Rhetorical Moves in Scientific Proposal Writing:
A Case Study from Biochemical Engineering
by
Brad Mehlenbacher
February, 1992
Submitted to Carnegie Mellon University, College of Humanities and Social Sciences in
partial fulfillment of requirements for the degree Doctor of Philosophy in Rhetoric and
Document Design.
Committee: Karen Schriver (Chair), Erwin Steinberg, David Kaufer
© Copyright 1992, Brad Mehlenbacher
1
Acknowledgments
Support from two sources allowed me to devote the better part of two years to the research
and writing of this dissertation—from a Digital Equipment Corporation/Carnegie Mellon
Fellowship and from the Engineering Design Research Center at Carnegie Mellon. As well,
the support of my committee members—Karen Schriver, Erwin Steinberg, and Dave
Kaufer—had a significant influence on my motivation to carry out the project and,
ultimately, on the final written product. Finally (and acknowledgment pages always seem
to beg our listing anyone we’ve ever known), I’d like to thank my family, Mom and Dad, for
continuing to ask me when I’m going to be finished, and Jeff and Barb and Emma, for not
asking me when I’m going to be finished. Special thanks to Mike Domach for his technical
expertise, guidance, and general irreverence; to Joseph Petraglia, especially, and to
Charlie Hill for their endless and (sometimes painfully) perceptive feedback on every
draft of every chapter; to Jim Palmer, Tom Duffy, and Maria Truschel, for making my first
two years at Carnegie Mellon as stimulating and as challenging as they were; to Jane
Kalbfleisch, for helping me survive the dissertation-writing process; and to Carole
Chaski, Nancy Penrose, Steve Katz, Mike Carter, and Carolyn Miller at North Carolina
State University, for sheltering me from committee work while I finished the final
chapters. Also, thanks to Elizabeth, Bill, and Gary and everyone at the Balcony for
infusing a little jazz into the dissertation-writing process.
2
Table of Contents
Abstract.............................................................................................................................5
Chapter 1—Introduction.....................................................................................................7
Chapter 2—Previous Research on Scientific Discourse.........................................................17
Characterizing Scientific Proposal Writers............................................................18
A Description of Science Adapted from Cognitive Psychology......................19
A Description of Science Adapted from Organizational Behavior................22
A Description of Science Adapted from the Sociology of Science...................25
The Historical Dichotomy Between Science and Rhetoric........................................28
The Contemporary Rhetorical Interest in Scientific Discourse..................................33
The Interaction Between Cognition and Context...........................................35
The Interaction Between Process and Product...............................................36
The Interaction Between Description and Prescription.................................38
Acknowledging the Role of the Proposal in Science..................................................42
General Conclusions................................................................................................49
Chapter 3—Two Pilot Studies of Scientific Proposal Writing..............................................50
A Talk-Aloud Study of Research Proposal Writing.................................................51
The Participants........................................................................................51
The Task....................................................................................................51
Classifying the Protocols............................................................................52
Issues That Emerged from the First Pilot Study.......................................................54
Defining an Audience for the Research Proposal..........................................55
Approaching and Organizing the Research Proposal...................................58
Constructing a Professional Ethos................................................................61
Focusing on the “Noise” that Enters Protocol Data.......................................62
General Conclusions....................................................................................65
Bringing Context into the Study of Proposal Writing...............................................67
The Participants........................................................................................67
The Open-ended Interviews........................................................................67
Issues That Emerged from the Second Pilot Study....................................................68
The Organizational Politics of Proposal Funding.........................................68
The Interaction Between Proposals, Funding, and Research..........................71
Differences Between Funding Sources..........................................................73
The Continuum from Proposal Funding to Technology Transfer......................75
General Conclusions....................................................................................78
Implications of the Pilot Studies for Research on Proposals.....................................79
Chapter 4—A Case Study from Biochemical Engineering.....................................................83
Data Sources and Collection...................................................................................86
A Participatory Design Approach to Data Collection..............................................90
Data Coding and Analysis......................................................................................93
Analysis of the Collaborative NIH Proposal..........................................................96
Analysis of Raymond’s Initial Proposal Effort........................................................98
Analysis of the Journal Article...............................................................................98
Collected Iterations on Data Interpretations...........................................................99
3
Table of Contents, Continued
Chapter 5—Results of the Case Study.................................................................................101
Raymond’s Background and Research Interests........................................................101
Raymond’s Context for Writing...............................................................................104
Raymond’s “Web of Writing”.................................................................................107
The Collaborative Proposal-Writing Project...........................................................120
Raymond’s Initial Proposal-Writing Effort.............................................................125
Raymond’s Earlier Journal-Article Project...............................................................128
Managing the Collaborative Proposal Project..........................................................134
The Fourteen Proposal Drafts.....................................................................134
Writing and Re-writing the Proposal’s Specific Aims Section......................138
Exchanging Notes to Aid Collaboration......................................................141
The Two Taped Meetings............................................................................145
Limitations of the Case Study................................................................................148
General Conclusions and Remarks...........................................................................151
Chapter 6—Discussion and Implications.............................................................................155
Methods as Windows on Proposal Writing..............................................................161
Scientific Proposal Writing as Storytelling.............................................................163
Scientists and Engineers as Rhetors.........................................................................173
Implications for Research and Teaching..................................................................179
Appendix A—Schriver’s Agenda of Research Questions..........................................183
Appendix B—Instructions for Taping a Protocol.......................................................185
Appendix C—Questions Asked of Fifteen Academic Researchers.............................186
Appendix D—The Episodes and the Multiple Data Types.......................................187
Appendix E—Questions Asked of the Biochemical Engineer....................................188
Appendix F—Chronology of Raymond’s Writing Projects.........................................189
Appendix G—Results of the Data Analysis.............................................................190
Appendix H—Chronology of the 14 Proposal Drafts................................................206
Appendix I—Evolution of the NIH Proposal’s Specific Aims Section.......................207
Appendix J—Evolution of the Proposal’s Three Major Sections.................................222
Bibliography.....................................................................................................................224
Vitae.................................................................................................................................257
4
Abstract
Rhetorical Moves in Scientific Proposal Writing:
A Case Study from Biochemical Engineering
Brad Mehlenbacher
Proposal writing in the sciences and engineering has only recently
received attention by researchers interested in rhetoric and writing. In
this dissertation, two pilot studies are introduced. The first is based on
fifteen talk-aloud protocols of professional writing students and, the
second, on fifteen open-ended interviews with academic researchers from
various fields. Both studies, while offering insights into the nature of
proposal
writing,
raise
important
issues
that
require
further
investigation. In particular, the studies reveal the need for research that
describes the following: (1) how goals, intentions, and plans interact with
contextual constraints and opportunities; (2) how writing processes and
written products are produced over time, and; (3) how descriptions of the
proposal-writing process can be used to inform current scientific and
technical writing pedagogy.
A third study aimed at addressing these issues is then described.
This study, of a biochemical engineer writing research proposals, extends
over two years. Based on multiple data-collection techniques, the study
expands our current understanding of the proposal-writing process.
It
reveals that proposal writing, journal writing, and laboratory activities
5
are interdependent. Proposal writing in biochemical engineering is a
dynamic process in which academic researchers negotiate numerous
constraints—between their characterizations of the proposal’s perceived
audience and that audience’s reaction to their text, between the proposal
format and discourse conventions of the field, and between their texts,
research goals, and the goals of their collaborators. Proposal writing is
not, as some researchers have suggested, an activity that takes place
prior to scientific research and publication.
Instead, in writing a
proposal, scientists must make numerous rhetorical choices regarding the
presentation of existing data, of their research experience, and of their
research intentions.
Importantly, applying different methodological approaches to
the study of writing in biochemical
engineering presents different
“windows” on the proposal-writing process.
Finally, I argue that
rhetoricians and sociologists are guilty of “objectifying” scientific and
technical writers—that is, of treating them as non-reflexive and arhetorical—when, in fact, we may gain a better understanding of their
sensitivity to rhetorical issues by studying their writing processes in
collaboration with them.
6
Chapter 1—Introduction
. . . now increasingly, scientists [have] to demonstrate their analytic
skills in planning and writing extensive proposals for well-thought-out
projects. They [have] to demonstrate their mastery of relevant literature
and techniques of research as well as argue their way around current
controversies in the field (58).
Mukerji, C. (1989). A Fragile Power: Scientists and the State. Princeton,
NJ: Princeton UP.
. . . the National Institutes of Health . . . during 1989 funded 27 percent of
the research proposals it received. It’s estimated that percentage will
drop to 23 percent this year. In 1975, the NIH [National Institutes of
Health] . . . provided funding at nearly twice that rate—45 percent of its
applications (B1).
Niederberger, M. (1990). Science Research Funding Shrinks. The
Pittsburgh Press. Sunday, December 9.
Rhetoricians, social scientists, biochemical engineers, whoever; we’re all
basically in the same business—trying to account for uncertainty.
Notes taken during a conversation with Raymond, a biochemical
engineer.
Traditionally, the competitive nature of science has been de-emphasized in favor
of a picture of science that emphasizes its consensus-building and contributory nature. The
scientific enterprise, however, as numerous researchers in rhetoric, sociology, psychology,
and philosophy have made clear to us, is very much a “business” in which scientists
negotiate and compete—sometimes with intense aggressiveness—for limited human,
technological, and monetary resources. Only when sociologists and rhetoricians of science
have highlighted the raging controversies underlying historical and contemporary
7
scientific investigations (cf., Markle & Peterson, 1981; Mazur, 1981; Nelkin, 1978, 1979,
1987) have we begun to realize that all is not as it seems in the Mertonian tower of scientific
inquiry. The popular characterization of scientists, as disinterested and objective
observers, many now regard as a myth; at its very heart, science is a social and political
activity. And the funding process is perhaps the most explicitly political aspect of all (cf.,
Cole, Rubin, & Cole, 1977; Gustafson, 1975; Lawrence, 1978; Mitroff & Chubin, 1979).
Given the key role that funding plays in the development and extension of science,
it is somewhat surprising that research proposal writing—the activity of producing the
formal documents that are at the center of the funding process—has only recently received
attention by rhetoricians and writing researchers. There are two major explanations that
might clarify why this is so. First, the study of scientific and technical discourse has been
traditionally outside the “proper” domain of rhetorical analysis (Kelso, 1980; Overington,
1977; Prelli, 1989a; Wander, 1976; Weaver, 1970; Weimer, 1977). However, contemporary
rhetoricians like Richard E. Young (1978, 1987) and Carolyn R. Miller (1985) have called
for a theory of scientific and technical discourse as argument, and this mandate has
heightened the interest in applying rhetorical analyses to scientific and technical texts.
The second explanation for why few researchers have studied scientific proposal
writing is that most researchers have limited their analyses to the most visible and central
type of writing that scientists do—journal-article writing. After all, it is this writing,
scientists would contend, that communicates new knowledge to the field and contributes to
consensus-building in science; and it is, therefore, the type of writing that rhetoricians and
sociologists interested in science have tended to privilege (e.g., Bazerman, 1988; Bernhardt,
8
1985; Campbell, 1973, 1975; Gilbert & Mulkay, 1980; Gragson & Selzer, 1990; Gross, 1985,
1990a, 1990b; Harmon, 1989; Rymer, 1988; Swales, 1984; Swales & Najjar, 1987).1
In 1985, Mark Haselkorn asserted that although “very little empirical research is
conducted in the area of proposal writing, there is just enough to show what proposal
writing research can do and how desperately it is needed” (273). Ironically, in that same
year, Greg Myers (1985b) produced one of the first of such analyses. His studies of the
writing processes of academic biologists (1985a, 1985b, 1990) revealed that the relationship
between academic writing for publication and proposal writing for funding were strongly
linked. In fact, Myers (1985b) found that both biologists incorporated in their proposals
“passages from . . . article manuscripts” that he had studied in the past (598). In discussing
what he called the complex “web of writing” that makes up scientific, technical, and
professional discourse, 2 Myers (1990) pointed to the tension that his proposal writers
experienced “in their attempts to present their work as interesting” and yet simultaneously
“show that it is original and yet entirely in accordance with the existing discipline” (59).
Myers’ primary argument is that, although scientific articles are usually the
“central” focus of researchers interested in scientific discourse, in his opinion, the research
1
2
Moreover, it is interesting that every one of the analyses cited here emphasize the
introductions and, occasionally, the materials and methods sections of scientific
journal articles. The general consensus among these researchers is that scientists
construct a plausible story-line regarding their place in the literature, the potential
contribution of their study, and the means by which other scientists can replicate
their methodological procedures.
For the purposes of this dissertation, I have intentionally conflated the terms
scientific, technical, and professional discourse; numerous other expressions are
used to characterize studies of the workplace composing processes of professionals,
including writing in the professions, writing in nonacademic settings, pragmatic
writing, on-the-job writing, and so on. What most of these studies have in
common, in Debs’ (1989) words, is that “they document . . . the importance of
communication . . . in scientific and technological organizations” (33). In short, I
am interested in discussing writing as it occurs in the professions and, specifically,
the proposal-writing process. Henceforth, I will use the term “scientific writing”
as a rubric for the above types of writing.
9
proposal represents the most “basic” form of scientific writing that scientists do. His
contention is that
. . . for many scientists heading large laboratories, proposals are in one
practical sense the most basic form of scientific writing: the researchers
must get money in the first place if they are to publish articles and
popularizations, participate in controversies, and be of interest to
journalists. For these researchers proposal writing is by no means an
occasional administrative duty; it is a constant effort that may involve
approaches to a number of different agencies, that may take about a
quarter of the [scientist’s] working time, and that requires more and more
attention as grants are given for shorter periods, and fewer projects are
funded (41).
With the exception of Myers’ (1985b, 1990) studies, however, very little research
has examined the nature of scientific proposal writing, particularly its long-term
relationship with journal-article publishing, laboratory work and experimentation, and
the funding process in general. How do academic researchers characterize, for example, the
perceived audience of their research proposals? In turn, how does the perceived audience
for research proposals influence the organization and content of research proposals? How
does the proposal-writing process influence and alter scientific data-collection techniques
and laboratory practices? How do scientists negotiate between the tinkering and
“messiness” of actual laboratory practices and still adhere to rigorous scientific discourse
conventions (cf., Kaufer & Geisler, 1989)?
Bazerman (1988) has argued for the importance of studying the complex negotiation
“between individuals bidding to work on, modify, develop, elaborate, or apply part of [an
academic] theory and [the] employers, funders, editors, referees, critics, and audiences who
grant the researcher various powers to continue, publicize, and gain acceptance for their
work” (184). Figure 1 represents the different types of negotiation that face scientific
proposal writers. Because of my interest in technical, as well as scientific settings, I have
10
extended Bazerman’s (1988) model to include the goal of theoretical and practical
contributions to knowledge.
In Negotiation With
employers
With the Intention of
accepting
continuing
Existing
elaborate
theory
funders
modify
develop
editors
Bidding To
Scientific
and
Technical
Researchers
extend
work on
apply
practice
enhance
critics
extending
audiences
review panelists
publishing
referees
Figure 1: The complex interactions that face scientific and technical proposal writers;
adapted from Bazerman (1988).
Figure 1 is deliberately designed to be read in two directions: either from the
scientific and technical researcher out or from the scientific community in. Thus, scientific
and technical researchers are constantly bidding to work on, elaborate, cultivate, extend,
fine tune, or apply existing theories and practices with the intention of extending,
continuing, publishing, or accepting existing theory or practices in negotiation with editors,
employers, audiences, funders, critics, review panelists, and referees. For example, two
dominant theories that biochemical engineers are currently interested in exploring are the
view of enzyme structures as being domain independent versus the view that enzyme
structures are heterogeneously organized; however, because the biochemical engineer that I
studied is interested in combining the two theories, he must make a painstaking argument
11
for the inadequacy of applying either theory in isolation (see Chapters 4 and 5). Or, in the
case of four of the academic researchers interviewed in Chapter 3, researchers can bid to
enhance current computer storage capabilities, an activity which is usually defined as
being “more applied” than theoretical in nature.
It is notable that Bazerman’s framework for future research on the construction of
scientific research and writing de-emphasizes the important role that technology and
instrumentation play in science. Perhaps this oversight is the result of the commonly held
belief that there are sharp differences between scientific goals (i.e., knowing that) and
technological goals (i.e., knowing how) (cf., Miller, 1985; Skolinowski, 1966). Miller, for
example, in her (1985) article “Invention in Technical and Scientific Discourse: A
Prospective Survey,” cites Hannay and McGinn’s (1980) argument that science is the
business of creating knowledge and technology is the business of creating products or
processes. I would argue, however, that the dichotomy between science and technology is,
as with all dichotomies, generally problematic. To say that scientists are motivated to
explain nature and that technologists are motivated to build tools is to de-emphasize the
critical interaction between equipment and observation. After all, in his discussion of
Compton’s classic research program, Bazerman (1988) notes that Compton was “constrained
by what mathematics, logic, and prior well-established theory allow one to say, by w h a t
available equipment can do, and by what data actually turned up” (200) [Italics added].
12
The dichotomy between scientific and technological practice has been further
blurred given the emergence of a significant number of sub-disciplines or specialty research
areas (e.g., applied physics, biochemical engineering, etc.), since it is generally difficult to
label their concerns as being strictly theoretical or strictly practical. Janich, in his (1978)
article “Physics—Natural Science or Technology?” argues convincingly that traditional
distinctions between scientific inquiry and technological “tinkering” are problematic since
scientific data are never collected without scientific machinery and since an understanding
of scientific machinery inevitably informs, influences, and constrains scientific knowledge
claims. He points out that “doing experiments is more an activity to produce technical
effects, which can be described appropriately as engineering rather than as a scientific
activity, properly speaking, as a construction of machines rather than as an inquiry into
nature, as an attempt to produce artificial processes or states rather than as a search for
true sentences” (11). To Janich, Scientific inquiry is therefore more accurately described as
“the technology of measurement and the technology of observation” (21).
Gökalp (1990), as well, has discussed the complex interaction between
instrumentation, experimentation, and theoretical research in science. He argues that “one
of the major influences of . . . new techniques has been to increase interactions between
experimental and theoretical lines of work at several levels—the work place, the
individual, and the cognitive structure of new research lines” (298). Given this perspective,
then, it seems probable that one of the reasons scientists are currently interested in
documenting the structure of quarks (rather than the structure of atoms) is because they
have access to equipment that allows them to “see” quarks.3
3
This observation has been made by numerous rhetoricians and sociologists
interested in the construction of scientific knowledge (Bloor, 1976; Campbell,
1975; Collins, 1982; Knorr-Cetina, 1983), but it is also notable that scientists
and engineers (at least the ones that I have interviewed formally and informally) are
13
In addition to calling for the study of scientific and technical researchers,
Bazerman’s (1988) model emphasizes another crucial aspect of the bidding process in
science—that is, the audience or audiences that evaluate scientific bids. Price (1986) has
identified the complex formal and informal communication networks that operate in science
(particularly between scientists and their journal reading community), and I would extend
his discussion of scientific audiences to include funders, editors, referees, administrators,
peers, graduate students, colleagues, employers, and other potential audiences. Bids, then,
are “submitted” to these numerous audiences in a variety of forms, from informal
conversations in the laboratory hallway to formal experimental or theoretical articles sent
to refereed academic journals.
Finally, the goal or result of this bidding or process of negotiation is the extension,
publication, acceptance, or continuation of the proposed research, theory, or practical
application. This extension, of course, feeds directly into existing theory and practice and,
in turn, informs future theory and practice. Indeed, one of the key relationships that I
explore in this dissertation is the relationship between proposal writing and scientific and
technical research. As I pointed out earlier, the common characterization of the
relationship between scientific research and writing tends to privilege, first, scientific
research activities and, second, the scientific journal article. Where scientific research
activity is the central focus, scientific discourse is often cast as either the non-problematic
communication of scientific findings or as a deceptive mask that hides scientific activities.
And where the scientific journal article is the central focus, other types of scientific
well aware of the practical and theoretical strengths and weaknesses of the
equipment they use; indeed, their formal discourse is structured to include, in the
limitations section, considerations of—not only reliability, generalizability, and
validity—but also the limitations of their data-collection equipment.
14
discourse such as the laboratory notebooks, sketches, doodles, notes, or research proposals
written by scientists, are relegated to the background.
Proposals, however, are not simply documents that are produced “after the facts
are established or well worked out” (as one scientist I interviewed characterized his
experience writing proposals). Rather, the process of writing a research proposal—as with
any composing effort—must surely influence or inform the research being represented in the
proposal. Chapter 5 presents my findings in regard to the relationship between proposals
and scientific research.
Finally, adapting Bazerman’s model or framework for future research interests me
for two reasons. First, it suggests that science is both a cognitive and a social enterprise.
That is, scientific and technical researchers are placed at the heart of the model and are
surrounded by a myriad of social constraints and potential audiences. And second,
Bazerman’s model implies that we still have a great deal to learn about discourse in science
and points to the challenging task that rhetoricians interested in science and technology
have set for themselves.
Thus the need for an exploration of the research proposal as rhetorical negotiation,
an exploration which begins to answer some of the following important questions: How do
academic researchers plan, write, and revise proposals for research funding and how does
the process of proposal writing shape academic research activities? What types of
rhetorical moves do academic researchers engage in when they produce proposals for
research funding? How does the research proposal as form enable and constrain academic
discourse and knowledge? How do scientists characterize their audiences and how do those
notions of audience influence the writing of research proposals?
15
Chapter 2 presents a detailed literature review which draws on research from
cognitive science, academic and nonacademic writing research, the sociology and history of
science, and the rhetoric of scientific and technical discourse. A detailed argument is be
made for why scientific and technical writing, in general, and proposal writing,
specifically, have normally been de-emphasized as objects of inquiry by writing
researchers. In particular, two exemplary studies will provide the starting point for my
discussion of proposal writing in science and engineering—Greg Myers’ (1985b, 1990) “The
Social Construction of Two Biologists’ Proposals” and Jone Rymer’s (1988) “Scientific
Composing Processes: How Eminent Scientists Write Journal Articles.”
16
Chapter 2—Previous Research on Scientific Discourse
The pieces all fit together, and they . . . were fragments at the beginning,
and what’s interesting is that each section is almost an independent unit
in itself. . . . And so each section is almost like a microcosm of the entire
piece. So within each section I . . . [am] looking for order, fitting it
together, and then I’m really not sure how the various pieces are going to
fit together, so I work on the pieces . . . and then I’m going to put it
together (interview with Subject-Scientist J, 226).
Rymer, J. (1988). Scientific Composing Processes: How Eminent Scientists
Write Journal Articles. Writing in Academic Disciplines: Advances in
Writing Research, Vol. 2. D. A. Jolliffe (Ed.). Norwood, NJ: Ablex, 211250.
So we wrote it to the audience I described and, you know, wrote kind of
defensively like you try and do in science. You see something. What are
you seeing? Is it real?
First open-ended interview with Raymond, a biochemical engineer.
In this chapter, I will begin by characterizing my object of inquiry, that is, the
proposal-writing scientist and his or her context for writing. To do so, I draw on literatures
from cognitive psychology, organizational behavior, and the sociology of science.4 I then
outline why the issues I am interested in have been ignored historically by rhetoricians
and writing researchers. This is followed by a review of numerous contemporary studies of
4
I recognize that, in separating the research and literature of these disciplines, I run
the risk of reducing or de-emphasizing the many issues they have in common.
Gross (1990), as well, observes that it is getting more and more difficult to
identify traditional disciplinary boundaries: “Thirty years ago the humanistic
disciplines were more easily definable: historians of science shaped the primary
sources into chronological patterns of events; philosophers of science analyzed
scientific theories as systems of propositions; sociologists of science scrutinized
statements aimed at group influence (Markus, 1987, 43). In the last too decades,
however, the humanities have been subject to what Clifford Geertz has called ‘a
blurring of genres.’ As a result, ‘the lines grouping scholars together into
intellectual communities . . . are these days running at some highly eccentric
angles’ (1983, 23-24).”
17
scientific and technical discourse emphasizing, in particular, the literatures from the
sociology, psychology, and rhetoric of science. Finally, I outline the need for a study of
proposal writing in science and set the stage for Chapter 3—the description of two pilot
studies of proposal writing and the research funding process.
Characterizing Scientific Proposal Writers
I want to begin my investigation by characterizing a proposal-writing researcher in
charge of numerous graduate students and a well-equipped laboratory in a university
setting. Not only is the researcher faced with a highly institutionalized, competitive
academic challenge, but he or she is also constantly in search of new and relevant sources of
research funding. And an integral part of the scientific funding process is the writing of
proposals for research funding. As Eaves (1984) asserts,
Whether referred to as “grantsmanship” or “researchmanship,” the
scholarship required for a successful research-grant application is as
demanding as that for a lecture, a report for publication, or a textbook.
Preparation of a grant application is a scholarly endeavor that combines
the values of a scientist and the skills of a scholar: dedication,
enthusiasm, standards of excellence, intellectual honesty, ethicality,
disciplined thinking, and clear writing (151).
To complicate things further for the researcher, proposal writing in the academy is
no longer an individual endeavor; rather, it is a complex social process.5 Academic
researchers often interact in large organizational networks that might include, not only the
corporate and federal funding agencies themselves, but also their peers, students, and
academic funding representatives. What, then, are the exigencies facing the proposalwriting researcher? How does the academic researcher plan and manage the collaborative
nature of the proposal-writing process? How does he or she characterize the intended
5
See LeFevre (1987) for an explication of the contemporary rhetorical view that
invention is a social, rather than an individual, endeavor.
18
audience or audiences for the proposal, especially given the increased competition for
federal and corporate funding (Kenward, 1984; Mandel, 1983)?6
A Description of Science Adapted from Cognitive Psychology
Cognitive psychology gives us an excellent starting point for any discussion of
scientific writing in context. The literature on problem-solving helps us describe the
researcher’s relationship with his or her environment. That is, any individual researcher
can be characterized as a symbol-making, symbol-using “system” working within a complex
environment where both the system and the environment are informed by one another.
Thus, the researcher operates as a problem solver, that is, he or she attempts to
discover—through varying combinations of trial, error, and selectivity—accurate state
descriptions and process descriptions of some element of nature (Newell & Simon, 1972).
Moreover, the researcher’s problem space is an ill-structured one, consisting of complex and
changing problems, goals, sub-goals, and the researcher’s existing knowledge of the
solution constraints (cf., Simon, 1979; Voss, Greene, Post, & Penner, 1983).
In addition, as with scientific activity in general, the production of scientific
discourse is an ill-structured problem, that is, it offers no single solution path, no
checkmate (Kotovsky, Hayes, & Simon, 1985; Pennington, 1985; Spiro, Vispoel, Schmitz,
Samarapungavan, & Boerger, 1987). It is what Chi, Glaser, and Rees (1982) call a “real
world problem” and, as such, “presents new obstacles that were not encountered previously
6
The epigram from the Pittsburgh Press that introduces chapter 1, for example,
estimates that the NIH funded 23 percent of its applicants in 1990, a drop from 45
percent in 1975 (cf., Novello, 1985, who estimates that approximately 50 percent
of all grants received by the NIH in 1972 were funded, as compared to 37.3 percent
in 1984, 281). De Bakey (1976), too, has pointed out that the NIH funded as
much as 50 to 60 percent of the applications it received in 1976 (5). And Mitroff
and Chubin (1979), referring to the National Science Foundation (NSF), cite the
growing interest in scientific peer review as stemming, in part, from the new
competitive funding situation (199).
19
in puzzle-like problems” since “the exact operators to be used are usually not given, the
goal state is sometimes not well defined” and “a large knowledge space” is essential (7).
That is, the agenda and goals of a productive academic researcher inevitably evolve as he
or she continues to collect and integrate new information over time.
Our proposal writer, then, is embedded in a complex task environment and faces
multiple exigencies—he or she must contend with methodological constraints, conflicting
representations of scientific and technical phenomena, existing research opportunities and
trends, graduate student and laboratory management, and so on. Simultaneously, our
researcher must attempt to construct his or her audience’s criteria for success, “why would
the NIH want to fund my research?”, and emphasize or de-emphasize research issues
according to the interests of the faculty, college, and academic discourse community in
general. In Bazerman’s (1988) words, “. . . even while the literature, research program,
problem formulation, experimental design, and data constrain the solution’s formulation,
all these earlier constraints are presented in the context of a formulation of the world that
takes the findings for granted” (202).
Like the literature on problem solving in cognitive psychology, the literature on
scientific discovery processes provides writing researchers with a vocabulary for
approaching scientific and technical invention, heuristics, and problem solving (e.g.,
Mansfield & Busse, 1981). Specifically, Simon and his colleagues have done numerous
studies of scientific discovery procedures (Bhaskar & Simon, 1977; Bradshaw, Langley, &
Simon, 1983; Kulkarni & Simon, 1988; Langley, Simon, Bradshaw, & Zytkow, 1987;
Langley, Zytkow, Simon, & Bradshaw, 1983). Their findings describe how scientists
represent data, develop hypotheses, design experiments, and generate new research
20
problems. Their findings, however, de-emphasize the role that texts and, in particular,
proposals for research funding, play in scientific communities.
In their study of Hans Krebs’ research on glutamine synthesis, for example,
Kulkarni and Simon (1988) argue that most scientific problem solving is guided by general,
rather than domain-specific, heuristics. That is, whether one is observing a chemist,
biologist, physicist, or enzymologist, many of the discovery procedures used by the
scientists are the same. Most importantly, Kulkarni and Simon (1988) assert that “the
step-by-step progress of Krebs toward the discovery of the urea cycle” was “produced by a
whole sequence of tentative decisions and their consequent findings, and not by a single
‘flash of insight,’ that is, an unmotivated leap” (174). This conclusion undermines
traditional perspectives towards scientific activity and discovery as “magical” or based on
unobservable insights.
Langley (1981), as well, describes the scientific discovery process as consisting of
general heuristics. The most effective heuristics used by scientists, she writes, lie in their
abilities to detect consistencies and trends in their data, to generate and re-generate
different hypotheses, and to draw on numerous theoretical terms and concepts. And
Bhaskar and Simon (1977), in an earlier study of a chemical engineer solving
thermodynamics problems, characterize scientific problem-solving behavior as a variation
on means-ends analysis, that is, where the scientist observes “a difference between the
present state of the problem and the desired goal state” and works towards reducing the
difference between the two states (203).
While the above characterization of scientists and scientific behavior adapted
from cognitive psychology provides us with many useful insights into the nature of
21
scientific activity, it does, however, de-emphasize two aspects of importance to
researchers interested in the rhetoric of science. First, the literature from cognitive
psychology completely ignores texts and their role in the construction of scientific
knowledge. Second, it de-emphasizes the role that collaboration and group dynamics play
in contemporary science and engineering.
In the next sections, I discuss the literatures from two fields, organizational
behavior and the sociology of science, and outline how they can contribute to what we know
about scientific and technical discourse.
A Description of Science Adapted from Organizational Behavior
As with the literature from cognitive psychology, writing researchers have also
begun to draw on literature from organizational behavior. One interesting line of research
is Harrison’s (1987) work. Harrison argues convincingly that writing researchers and
organizational behavior researchers have numerous interests in common, specifically, an
interest in how context informs a writer’s discourse, beliefs, and methods of argumentation
and consensus-making. She notes that the interaction between cognition and context is a
reciprocal one since writers inevitably shape and alter the organizational environment
surrounding them. A study of the organizational contexts within which writers work,
according to Harrison, should provide researchers interested in writing in the disciplines
with a view of organizations as systems of knowledge and as patterns of discourse which
act and are acted upon by the individuals working in them (cf., Bazerman’s, 1988,
sociopsychological characterization of science discussed in chapter 1). Harrison (1987) also
believes that viewing writing as a situated and complex social activity has important
implications for writing pedagogy. She concludes that “To take seriously the notion of
22
context is to build in students an appreciation for the idiosyncratic nature of terminologies,
semantic systems, beliefs and values, and reasoning processes that characterize any
interdependent social grouping” (19).
Nystrand (1989), too, has called for a definition of composing that views “each act
of writing [as] an episode of interaction, ideally exhibiting intertextuality . . . with a
particular scholarly community or discipline typified by particular premises, issues, and
givens” (70). In his (1989) article, “A Social-Interactive Model of Writing,” Nystrand
elaborates on a view of composing as negotiation. “Communication,” he argues, “begins as
an initial calibration of conversants’ intentions and expectations vis-a-vis the topic and
genre of the text, and the discourse is largely structured by the conversants in terms of each
other’s evolving perspective on the topic and the discourse itself; it is in this sense that we
may speak of discourse as negotiated by the conversants” (73). His perspective towards
writing as situational and social, in turn, foregrounds the importance of contextual
constraints (or what he calls misconstraints) on the writing process. He defines three types
of misconstraints: (a) inadequate elaboration at the level of topic results in abstruse text,
that is, a text that says too much about too few points; (b) inadequate elaboration at the
level of comment results in ambiguous text, or text that says too little about too many
points; and, (c) inadequate elaboration at the level of genre results in misreading (80). This
view towards writing and the contexts within which writing occurs, Piazza (1987) points
out, is based on a conversational model and stresses how “writers must negotiate key text
points and choose appropriate text options since these are guided by the need to share
knowledge and maintain a balance of discourse between reader and writer” (116) (Heath &
Branscombe, 1985; Nystrand & Himley, 1984).
23
Doheny-Farina (1986) also draws on the literature of organizational behavior to
outline his model of collaborative writing. He stresses that our knowledge of how
organizational contexts affect writing can be greatly improved if researchers document in
detail the behaviors of writers in nonacademic and scientific settings. Unlike Harrison
(1987), Doheny-Farina’s (1986) emphasis on the organizational settings within which
writers work, makes him a strong advocate for ethnographic research. To this end, he
argues that
Because any [writing] act can have multiple meanings, researchers seek
diverse interpretations of the acts under study. This can be achieved by
exploring participants’ actions from differing points of view, and
collecting data that concerns these actions through several methods
(163).
In conclusion, researchers interested in different contexts for writing have begun to
borrow from the field of organizational behavior. Given the social nature of the writing
process, these researchers argue that we must understand group dynamics and their
influence on discourse production.7 And, since an interaction between writing and
organizational structure clearly exists, these researchers advocate a case-study-based
approach to studying writing in context (cf., Doheny-Farina, 1986, 1991), that is, a
methodology that facilitates the collection of detailed information about the
environments which constrain and enable writing in the workplace. As Doheny-Farina
(1986) asserts, such studies
. . . expand the definition of writing activity to include social interaction
as a part of the process. Instead of limiting the act of writing to the
moments when the writer encodes, research into the social process of
writing traces the writer’s activities through time, exploring how life
experiences impinge upon the rhetorical choices that writer makes (179).
7
See also, Brown and Herndl, 1986, and Herndl, Fennell, and Miller, 1991, for
discussions of communication and miscommunication in nonacademic settings and
their relationship with organizational structure.
24
A Description of Science Adapted from the Sociology of Science
In addition to drawing on research from cognitive psychology and organizational
behavior, several writing researchers have advocated the need for more “social”
descriptions of writing in academic and nonacademic settings; they argue that the
literature from sociology—particularly the sociology of science and technology—offers
researchers new insights into the behavior of writers in complex organizations. This
literature is so rich, in fact, that Faigley (1985) asserts that “It is tempting to import
wholesale the research issues raised in the sociology of science for the study of
nonacademic writing” (239). Similarly, arguing for the relevance of research from the
sociology of science, Myers (1986) points out that “the sociology of science could provide an
enormous body of evidence for the limitations of the cognitive approach and suggest
methods and perspectives for further work” (596).8 Both Faigley (1985) and Myers (1986),
while acknowledging that sociologists have tended to ignore the role discourse plays in
studies of science and engineering, clearly view research in the sociology of science and
technology as one means for writing researchers to gain a better understanding of the
complex practices of contemporary researchers.
Certainly, not all sociologists of science have ignored the role of the text in
scientific practice and inquiry. Three studies of particular note are Gilbert and Mulkay’s
(1984) “Opening Pandora’s Box: A Sociological Analysis of Scientists’ Discourse,” Law and
8
The debate between cognitivists and social constructivists is an on-going and
complex one, and outside the province of this discussion. Nystrand (1989), for
example, has argued that cognitive theories of the writing process tend to
emphasize planning and goal-setting, and ignore the relationship between
processes and products, between reading and writing, and between problem solving
and environmental constraints (see, also, Berkenkotter, Huckin, & Ackerman,
1991; Bizzell, 1982a; Bruffee, 1984, 1986; Carter, 1990; cf., Flower, 1989b, for
an integrative view towards the cognitive and social dimensions of writing).
25
Williams’ (1982) “Putting Facts Together: A Study of Scientific Persuasion,” and Latour’s
(1988) “A Relativistic Account of Einstein’s Relativity.”
These and other sociologists of science have posited related theories of how
scientists maintain an “objective stance” when composing scientific journal articles. Latour
and Woolgar (1979), for example, describe how scientists must painstakingly add numerous
“modalities”—that is, qualifications—to their texts in order to create personas that are
not claiming to be stating facts. Latour (1988) describes how Einstein’s text can be viewed
using the semiotic constructs of shifting in and shifting out. Scientists attempt, in Latour’s
(1988) opinion, to shift out (i.e., to take the distanced, objective tone of rational observers)
in order to move attention away from them, as actors, and to focus attention on the objects
that they are describing. Finally, Pinch (1985) describes how scientists must negotiate
between internality and externality when constructing their texts; that is, as with Latour
and Woolgar’s (1979) added modalities, Pinch’s (1985) scientists cannot fully externalize
the objects they are describing but, rather, must couch their claims in existing theoretical
and practical knowledge.
The interaction between scientists, their texts, and the scientific claims embodied
by those texts is, however, not an explicit one. Gilbert and Mulkay (1984), for example,
point out that descriptions of the relationship between scientists and their ideas often
ignore the role that texts play in the process. In describing how scientists construct
consensus, Gilbert and Mulkay (1984) posit that scientists attempt to “treat each [scientific]
viewpoint as clearly evident in a scientist’s written products and informal statements” and
to “treat the view of (most) individual scientists as coinciding with one of the current
theoretical labels” (138). In this way, texts—whether they are scientific research articles
or proposals for research funding—are omitted from the picture of the scientific enterprise.
26
Meaning is transferred from the text to the scientist and to his scientific community, and
“theoretical labels” are free of the form by which they are communicated. Texts and
scientists are transformed into theoretical labels and, hence, relegated to the background of
scientific debate.9
Related to this research, sociologists of science who are interested in citation
practices have made similar claims. Gilbert (1977), for example, focusing on the
persuasive nature of citations, asserts that “they provide evidence and argument to
persuade their audience that their work has not been vitiated by error, that appropriate
and adequate techniques and theories have been employed, and that alternative,
contradictory hypotheses have been examined and rejected” (116). In this way, citations
act, not only to justify or account for the positions adopted by the authors, but also to
establish that the authors are forwarding a contribution to the existing literature. Law
and Williams (1982), similarly, describe how scientists “array people, events, findings and
facts in such a way that this array is interpretable by readers as true, useful, good work,
and the rest” (537). For this reason, they characterize scientific research articles as
interpretive networks, as “resources structured in such a way as to induce readers or hearers
to network them in an appropriate manner, ascribing high value to the array itself, low
value to facts that are held to be false, high value to the assumed truth, and so on” (552).
9
See Prelli (1989b) for a compelling exception to this rule. In his case study of the
controversy over the language capabilities of apes, Prelli cites Sebeok’s (1982)
systematic attack on Patterson and Linden’s (1981) scientific ethos rather than
their theoretical arguments. Sebeok asserts that their claims should be ignored
because they do not belong to the appropriate scientific community, because they
do not belong to an accredited institution, because they receive “minor grants from
small Foundations,” and because they did not “submit their claims for
authorization by competent scientists” (Prelli, 1989b, 56).
27
In conclusion, the literatures from cognitive psychology, organizational behavior,
and the sociology of science offer rhetorical theorists and writing researchers various ways
to begin to describe scientists, scientific settings, and scientific discourse. In the next
section, I provide a brief overview of the historical relationship between rhetoric and
science. In particular, I discuss some of the reasons that science and scientific discourse
have traditionally been outside the scope of rhetorical analysis which, in turn, will
clarify why many of the issues I am interested in exploring are, in part, a result of the
contemporary rhetorical interest in scientific and technical discourse.
The Historical Dichotomy Between Science and Rhetoric
Research in the sociology and rhetoric of science and technology is a recent
development and has posed some difficult and, as yet, unanswered questions. For example,
what are the norms of scientific and technical discourse? How do these norms function? Do
they function in different ways for different scientific discourse communities? How are
academic writers informed by these norms or constraints? How do academic audiences
interpret these norms? One of the major reasons that these are relatively recent questions
is that our contemporary conception of rhetoric differs from traditional conceptions of
rhetoric in two important respects. First, rhetoric is no longer directly associated with
persuasion but, rather, has come to be viewed as a collective, collaborative, epistemic
activity (cf., Burke, 1945). Second, as Burke (1978) has argued, “many questions are called
‘rhetorical’ precisely because there is no ‘truth’ to which one can refer” (16).
Our recognition of the contingent nature of meaning-making has allowed us to
expand traditional rhetorical conceptions of scientific and technical discourse. As Miller
and Selzer (1985) point out,
28
[That] contemporary philosophers and historians of science . . . have
called into question Aristotle’s separation of the sciences from rhetoric
suggests the possibility of a similarly expanded conception even a
scientific one, are often disputed and that syllogistic logic is insufficient
to account for the development of a discipline (Kuhn, 1970; Toulmin,
1972). Since the premises of science are matters for debate, the discourse
of the disciplines (including scientific and technical disciplines) has
become a part of the contemporary conception of rhetoric (312).
Tracing this development historically, Zappen (1987) concludes that “Recent
studies in the rhetoric of science and technology owe much of their impetus to research in
the history and philosophy of science and technology, which has undermined the logical
positivist assumption of certainty in science and set in its place notions of science and
technology based upon their concern with probabilities and with audiences, especially
communities of specialists” (288).
Works of particular relevance from the history and philosophy of science include
some of the following: first, Kuhn’s (1970) “The Structure of Scientific Revolutions” is
regarded as seminal because of its assertion that scientific knowledge is not produced
logically and incrementally, but rather, through argumentation, consensus, and
commitment. Second, Toulmin’s (1972) “Human Understanding” explicitly addresses the
decay of positivism and the question of how one chooses a world-view. As Miller and
Selzer (1985) have pointed out, individuals like Kuhn and Toulmin have reinforced the
notion that “Since the premises of science are matters for debate, the discourse of the
disciplines (including scientific and technical disciplines) has become part of the
contemporary conception of rhetoric” (312). And finally, Rorty’s (1979) “Philosophy and
the Mirror of Nature” goes a step further than Kuhn and Toulmin and discusses a l l
knowledge as socially constructed. Knowledge, to Rorty, is “what society lets us say” and
“what . . . is good for us to believe” (12-13).
29
Importantly, a view of science and engineering that is based on the notion of
probabilities and uncertainty, and which stresses the contingent nature of scientific
“truths” and “facts,” does not necessarily result in anarchy or chaos (cf., Feyerabend, 1975);
particularly if that view of science emphasizes the constructive, argumentative nature of
knowledge-making in science and engineering. A rhetorician interested in science and
technology, therefore, is primarily driven to document and understand how research
processes and, more significantly, scientific texts, operate to contribute new knowledge
while simultaneously building community consensus.
Another, related historical development, as numerous researchers have pointed
out, is that traditional definitions of the province for rhetorical inquiry have largely
ignored invention and discovery and focussed, instead, on form and arrangement (Crowley,
1985; Hairston, 1982; Young, 1978, 1987). In Berlin’s (1987) words, “current-traditional
rhetoric . . . was divided into two parts, the first dealing with superficial correctness
(barbarisms, solecisms, and improprieties) and the second with forms of discourse” (37).
And because current-traditional rhetoric emphasized textual elements, it, in turn, ignored
the role of readers, writers, and writing processes. As Berlin and Inkster (1980) assert, “the
tendency of the paradigm [was] to reduce the significance of the writer and to emphasize
the mechanical aspects of composition . . . even when the texts address[ed] a genre that
would characteristically elevate the importance of the writer” (12).
Before turning to the contemporary conception of rhetoric, and its relation to the
study of scientific discourse, it should be noted that these developments in rhetoric are not
entirely the result of developments in the history, sociology, and philosophy of science.
Myers (1986), for example, has correctly pointed out that, until as recently as the 1970s, the
sociology of knowledge concerned itself primarily with “how societies shape . . . systems of
30
belief” and “excluded science from its analysis, assuming that scientific facts were shaped
by method and the natural world, not by society” (597).
Contemporary shifts towards a more “relativistic” view of science and the study of
science (Chubin & Restivo, 1983; Collins, 1981b, 1982; Knorr-Cetina & Mulkay, 1983),
however, have undermined many of the assumptions of the “strong programme” in the
sociology of science (cf., Barnes, 1977; Bloor, 1976). While I favor many of the major tenants
of the new school of sociology, I do so with two important provisos.
First, some contemporary philosophers and sociologists of science run the risk of
over-emphasizing the chaotic, illogical aspects of scientific knowledge-making, thus
promoting a new version of the traditional strong programme’s “black-boxism” (cf., Collins,
1981a; Latour & Woolgar, 1979). That is, similar to composition’s romantic currenttraditionalists, contemporary sociologists of science must be careful not to eliminate
interesting areas of exploration (e.g., invention, creativity, and so on) by describing them as
mysteries without decomposable methodologies (cf., Rothenberg, 1979).10 Second,
although some sociologists of science have argued strongly for the integration and analysis
of scientific discourse (e.g., Gilbert & Mulkay, 1984; Mulkay, 1981; Mulkay & Gilbert,
1982a, 1982b, 1982c; Mulkay, Potter, & Yearley, 1983), the tendency in general has been to
emphasize “unmasking” scientific activity (e.g., Lynch, 1982; Studer & Chubin, 1980;
Travis, 1981), rather than to explore how scientific discourse functions to “mask” the
complexity of that activity. Recently, Collins (1981a) has called attention to the masking
function of scientific discourse when he describes “mechanism[s] of closure,” arguing that
10
See Richard E. Young (1978, 1987) for an excellent overview of the paradigmatic
shift in contemporary rhetoric from the current-traditional approach—which
ignores the role of invention and discovery in composing—to new conceptions of
rhetoric which emphasize invention and the social nature of discourse.
31
sociologists need to explore “the use of rhetorical and presentational devices by one group
of experimenters to make their own interpretation of the experimental series the one
credible possibility” (5).
The need for more detailed studies of scientific and technical discourse has been
well-established by numerous researchers over the last fifteen years (e.g., Anson &
Forsberg, 1990; Barnum & Fischer, 1984; Bazerman, 1988; Bernhardt, 1985; Blyler, 1989;
Brown & Herndl, 1986; Debs, 1989; Doheny-Farina, 1986; Fahnestock, 1986; Gilbert &
Mulkay, 1980; Gusfield, 1976; Harmon, 1989; Kelso, 1980; Mayer, 1985; Selzer, 1989;
Weimer, 1977; etc.). In the next section, I describe what researchers interested in scientific
and technical discourse have contributed to our understanding of scientific writers, their
writing processes, and the texts that they produce.
The Contemporary Rhetorical Interest in Scientific Discourse
As I argued in the last section, numerous researchers have begun examining, not only
the individual writer, but also the rhetorical context within which that individual is
situated (e.g., Bartholomae, 1985; Bizzell, 1988; Bruffee, 1986). Most research up to this
point has tended to focus on academic writing as it occurs in the classroom (e.g., Faigley &
Hansen, 1985; Herrington, 1985). However, another group of researchers have begun
examining the nature of writing in the academy, for example, the writing and reading
processes of biologists (Gragson & Selzer, 1990; Halloran & Bradford, 1984; Myers, 1985a,
1985b, 1990), of biochemists (Gilbert & Mulkay, 1984; Rymer, 1988), of engineers
(Herrington, 1985; Selzer, 1983; Winsor, 1989, 1990), and of physicists (Bazerman, 1984,
1988). Indeed, Miller and Selzer (1985), citing Kinneavy (1983), have argued that it is
crucial for rhetoricians to begin to “make some general study of the methodologies,
32
definitions, criteria of evidence, general axiomatic systems, and views of these value
systems” in various disciplines (309). And finally, significant attention has been turned to
writing in nonacademic settings, such as engineering firms, computer companies, hospitals,
and legal institutions (Anderson, Brockmann, & Miller, 1983; Brown & Herndl, 1986;
Harrison, 1987; Moran & Journet, 1985; Odell, Goswami, & Herrington, 1983; Schriver,
1989a; Selzer, 1983, 1989).
Researchers interested in scientific, technical, and nonacademic writing contend
that studying “real-world” writing expands the definition of context by examining the
relationship between writers, their social contexts, and the rhetorical choices available to
them (cf., Doheny-Farina, 1989). Other researchers emphasize how nonacademic writing
helps us to explore the function of discourse communities and how overlapping communities
affect discourse (Odell, 1985). Most importantly, these studies have continued to call for
pedagogical changes that better reflect actual professional writing practices.11
Ultimately, then, studying scientific writing raises a series of interesting questions:
How do academic researchers write proposals for funding and how the the proposalwriting process inform subsequent research efforts? How does the proposal as genre
empower and constrain academic knowledge and meaning-making? How do academic
researchers represent the audiences who will ultimately grant or refuse them the funding
necessary to continue their research?
11
See, for example, Gilsdorf (1986) who found that business communication
teachers tended to de-emphasize the teaching of persuasive writing despite its
widespread use in business settings, and Barton and Barton (1980) who argue that
“The provisional and transactional nature of professional roles must be recognized
by both engineering students and their instructors” (452).
33
These questions anticipate numerous issues currently being explored by
contemporary rhetoricians and writing researchers. Research in professional writing,
scientific and technical discourse, and other non-literary modes of communication, for
example, has stressed the need for studies that describe the relationship between writers’
goals, intentions, plans, and the various texts they produce. This is in response, in part, to
three general developments in contemporary writing research: the emphasis on
(1)
examining writing as both a cognitive and a social activity, that is,
studying writing and writers contextually,
(2)
describing the process of writing as well as tracing the development of the
written products resulting from those processes,
(3)
strengthening the interaction between descriptive studies (where the
intention is to document “what is” current practice in academic and
nonacademic settings) and pedagogical goals (where the intention is to
articulate “what ought to be”).
These three developments, in general, point to the need for what Nystrand (1989)
and Flower (1989) have described as an “Interactive Theory of Writing,” a theory which
integrates the social and the cognitive, products and processes, and descriptive and
pedagogical goals. Writing researchers, Flower (1989) contends, “need what
ethnographers describe as ‘grounded theory’ . . . —a vision that is grounded in specific
knowledge about real people writing in significant personal, social, or political situations”
(283).
34
The Interaction Between Cognition and Context
We now recognize the importance of studying the multiple goals experienced
writers set for themselves based on the complex and changing constraints placed on them in
different writing situations (Hayes & Flower, 1980; Kaufer, Hayes, & Flower, 1986).
What it means to be a “successful” writer clearly varies depending on the writer’s
knowledge base, audience awareness, genre familiarity, and a host of other cognitive and
social factors (Flower, Schriver, Carey, Haas, & Hayes, 1989; Hayes, Flower, Schriver,
Stratman, & Carey, 1987; Selzer, 1989). Broadhead and Freed (1986), too, have argued
that accounting for the interaction between social and cognitive constraints on the writing
process is crucial; unfortunately, they note, “. . . much of the discipline’s focus on cognitive
processes have tended to emphasize the autonomous writer, he or she who composes, not
within a system but by dint of well-oiled heuristics and problem-solving strategies, who
composes by freely negotiating among memory, text, reader, and world” (156). Brandt
(1986), as well, has asserted that the context within which writers compose “remains in
the background of most investigations of writing and writing processes, as a dark stage”
(140).
A notable exception to this is Doheny-Farina’s (1989) case study of an adult writer
working in both academic and nonacademic settings for writing; in the study, he elaborated
on numerous implicit and explicit constraints facing her as she moved from one writing
context to another.12 Certainly Scardamalia and Bereiter (1987) anticipated some of
12
For example, as an academic writer, Anna was expected to act as an authority
figure and to strive for novelty and originality; in the nonacademic community,
however, she was faced with a myriad of constraints, such as the external and
internal politics of the organization for which she worked. Anson and Forsberg
(1990), similarly, cite “a remarkably consistent pattern of expectation, frustration,
and accommodation” on the part of six university seniors as they came to
understand the differences between academic and nonacademic discourse (200).
35
Doheny-Farina’s (1989) findings when they defined unsuccessful writers as individuals
who produce texts that reveal numerous failings “such as lack of adaptation to audience,
lack of planning, and paucity of revision” (151). Because many of these shortcomings might
well be a factor of the particular setting within which discourse is produced, researchers
have begun to investigate the contextual and social factors that are inevitably brought to
bare on the writing process (Bazerman, 1984; Brandt, 1986; Gilbert & Mulkay, 1980;
Herrington, 1985; Miller, 1980; Odell, 1985; Piazza, 1987).
The Interaction Between Process and Product
The second general development in writing research, as Witte and Cherry (1986)
have pointed out, is that researchers now understand that the process movement in
composition has not been without its shortcomings; they argue that “One of the least
fortunate effects has been the frequent dichotomizing of process and product because of
difficulties encountered in drawing inferences about writing processes from written
products” (114). It appears that, in our eagerness to introduce the process model into
writing research, we have clearly de-emphasized the importance of understanding the
relationship between writing processes, writers, and the texts they produce (Applebee,
1986; Nystrand, 1989; Witte, 1987). Connected to this, Britton (1978) has suggested that “. .
. the most obvious lack [of research on composing] is that of an accurate matching of a fully
revised and edited piece of writing with a complete time record of its production” (28).
There are two possible explanations for why writing researchers have only begun
to emphasize the interaction between writing processes and written products in scientific
and technical settings. First, as I argued earlier, writing researchers have only recently
begun to recognize that such settings are viable areas for rhetorical inquiry. And second,
while there is clearly a need for studies that tie composing processes to the texts they
36
produce (Witte & Cherry, 1986), few writing researchers have drawn on the considerable
research being produced in discourse analysis, text evaluation, and sociolinguistics.13
These studies share a common perspective towards language and language use that
emphasizes finished products and readers’ reactions to those texts. However, because of
this emphasis, researchers often ignore the other end of the communication continuum—the
writers who produce those texts—and instead stress how texts might be improved to
increase reader comprehension. Recently, however, researchers have begun to explore how
our understanding of texts can be tied into our understanding of writing processes (Applebee,
1986; Nystrand, 1989; Witte, 1987; Witte & Cherry, 1986). Finally, having extended our
object of inquiry to account for the entire writer-text-reader continuum, researchers now
recognize the importance of developing methodologies that better capture those
relationships (cf., Doheny-Farina & Odell, 1985; Odell, Goswami, & Herrington, 1985).
The Interaction Between Description and Prescription
The third general development in writing research is, in many ways, a direct result
of our desire to broaden current definitions of composing. Ironically, despite the growing
body of studies describing writing in professional, scientific, and technical settings, some
researchers have complained about how little these studies have influenced writing
pedagogy and practice (e.g., Miller, 1989).
13
While a comprehensive survey of this research is impractical here, some more
notable efforts include Britton and Black’s (1985) research on expository text
comprehension, Charney’s (1987) research on discourse cues and reader-response,
Couture’s (1986) collection of essays on functional approaches to writing, Duffy
et. al.’s (1982, 1985, 1989) studies of text production and readability, Halliday’s
(1978) theory of the ideational functions of texts, Halliday and Hasan’s (1976)
analysis of text cohesion, Kintsch and van Dijk’s (1978) model of discourse
comprehension, Schriver’s (1989b) review of reader-oriented approaches to text
evaluation, and Vande Kopple’s (1982, 1985, 1986) functional perspective towards
metadiscourse and the pragmatics of written texts.
37
Again, the split between descriptive studies of writing and classroom practice is
partly historical in nature. That is, the current-traditional paradigm for writing excludes
process theory and, therefore, process studies of workplace composing practices are often
treated as redundant or impractical. Also, as some critics of the process movement have
pointed out, the dichotomy between processes and products continues to be supported in the
writing classroom (Applebee, 1986; Witte, 1987). That is, as advocates for process-oriented
instruction, we are still unclear about how teaching our students about their planning,
drafting, and revising processes actually translates into their finished texts. The major
assumption driving much of our teaching is that giving inexperienced writers knowledge of
“expert” composing strategies will subsequently improve their writing, despite conflicting
research on what exactly it means to “be an expert” (Carter, 1990), and on how much
expertise generalizes across different problem domains (Chi, Glaser, & Rees, 1982; Larkin,
McDermott, Simon, & Simon, 1980) versus how much expertise is particular and situated in
nature (Brown, Collins, & Duguid, 1989; Greeno, 1988; Mehlenbacher, Duffy, & Palmer,
1989; Mehlenbacher, 1992; Suchman, 1987). How, for example, can research on report
writing in different contexts (Brown & Herndl, 1986; Herrington, 1985; Miller & Selzer,
1985; etc.) be used to teach writers from different technical fields? Is there a general
report-writing process or product that transfers across alternative report-writing
situations, for instance, informal reports, reports written for funding agencies, or academic
reports?
In the light of these complex and difficult questions, it is not entirely surprising
that writing instructors have only recently begun to re-examine existing teaching practices.
Students, however, continue to be given style guides, algorithms, and specifications,
despite our awareness that writing is not easily proceduralized. And the emphasis on
38
product-oriented guidelines and writing advice continues to dominate current writing
pedagogy, despite well-documented problems with guidelines and specifications for
writing (Duffy, Mehlenbacher, & Palmer, 1989; Greeno, 1988; LeFevere & Dixon, 1986;
Marshall, Nelson, & Gardiner, 1987).
Alternatives to guideline-based instruction, however, are beginning to get attention
from writing researchers interested in bringing what we have learned about real-world
writing. Spiro, Vispoel, Schmitz, Samarapungavan, and Boerger (1987), for example, have
argued against prescriptive teaching methods in favor of case study-based methodologies.
Further, they point to the need for a theory of case or example sequencing, that is, a
rationale for how instructors order and present model cases to their students.
Yet other researchers have taken a different stance, arguing that students more
effectively transfer knowledge from one problem domain to another if different types of
examples are used as the instruction set (Bassok & Holyoak, 1985). In terms of writing
instruction, therefore, given the goal of producing a proposal for the NIH, the more
example proposals accepted by the NIH that students read, presumably the greater their
chance of producing a successful proposal (at least in theory).
Other researchers have advocated the need for an additional step in the use of
model texts. Mayer (1981, 1985), reviewing two instructional techniques—giving students
concrete models alone versus giving students concrete models and encouraging them to put
the information into their own words—found that groups that put information into their
own words recalled the material better overall.
Unfortunately, many questions regarding the use of model research proposals as a
pedagogical tool remain unanswered. How many models, and of what nature, for example,
39
are optimal for student understanding? Do counter-examples, or “unsuccessful” models,
help writers establish effective principles for future writing contexts? Do some model texts
contain a richer repertoire of principles for good writing and, if so, is there an optimal
number of principles that writers should be exposed to to improve transfer into subsequent
writing contexts? How might researchers who have collected process information integrate
their findings with model proposals?
Because I have collected multiple types of process and product data (see Chapters 4
and 5), I intend to explore how writing researchers—particularly those who have collected
naturalistic data on composing in different contexts—might begin to re-conceptualize
current, “static” guidelines and model texts (i.e., instructional specifications that tend to
ignore different contexts of use and to provide insufficient information on how they should
be applied). What are the pedagogical implications of using case-study data to build
“active exemplars,” that is, examples that integrate process and product information, as
well as pointing to cognitive and social issues that might influence a proposal writer’s
goals and intentions.14 Marshall et. al. (1987), for example, have argued that design
guidelines need to be extended to include examples, counter-examples, and cases where the
guidelines might or might not apply. A detailed case study seems like an excellent
database for writing researchers interested in building effectively “contextual” examples
for general instructional purposes and the teaching of scientific and technical writing.
14
Importantly, I am aware that no single case study of proposal writing is likely to
provide us with a completely representative set of model examples that transfer
across different contexts for writing; rather, I view such a case study as a startingpoint for documenting how proposal writing in one context differs from and is
similar to proposal writing in other contexts.
40
In the next section, I review some of the existing research on one genre of scientific
writing, the research proposal, and outline a study—the centerpiece of this
dissertation—aimed at contributing to our current understanding of the genre.
Acknowledging the Role of the Proposal in Science
The reasons for the absence of research on proposal writing are varied and complex.
In part, it is because academic discourse has been valued more than other forms of writing
(e.g., proposals, memos, advertising copy, and so on) (cf., Schriver, 1989a). Only recently,
in fact, have researchers begun to acknowledge that proposals may well be “the most
obviously rhetorical writing scientists do” (Myers, 1998b, 1990), and hence deserve further
study.
Yet despite the acknowledged importance of proposal writing in the sciences and
engineering, it is surprising how few researchers have studied the genre (Haselkorn, 1985).
Certainly, studies are beginning to appear (e.g., De Bakey, 1976; Freed, 1987;
Killingsworth, 1983; Mattice, 1984), but few have examined in detail the relationship
between academic writing for publication, scientific research, and proposal writing or, to
use Myers’ (1985b, 1990) expression, “the web of writing” that infuses every scientific and
technical setting.
Moreover, the studies of proposal writing that do exist tend to reinforce many of
the conceptions of scientific and technical writing that writing researchers are currently
trying to undermine. That is, the majority of the research on proposal writing tends to
characterize the activity abstractly and to prescribe guidelines based on anecdotal or
classroom evidence. For example, Mattice (1984) states that “It is important to remember
that while a proposal must be clear and objective, it must also be easily read” (6). Smith
41
(1976) argues that “it should be emphatically stated that the university can do a greatly
improved job of educating [potential proposal writers] in the concepts, terms, and
disciplines of English grammar” (117). De Bakey (1976), in distinguishing between
proposals and written research reports, makes the following assertion:
The temporal relation between the writing and the research, for
example, differs. You write the proposal before you know the results and
the report after. . . . The proposal is a forecast; the final report a
retrospection (8).
My contention, from the outset of my investigation of the proposal-writing process,
is that such characterizations of the process reinforce our tendency to devalue the role of
proposals in the construction of scientific knowledge. Certainly they cast proposals as
persuasive, but they disregard the complex interaction between proposals, scientific
research, and scientific journal-article writing. Instead of emphasizing how proposals
influence invention and discovery, they highlight grammatical details. Such
characterizations of proposal and report writing, in addition, reinforce the common
misconception that such writing is factual or objective; as De Bakey puts it, “When you
write the final report, . . . you have the results before you and so can write factually rather
than anticipatorily” (8).
Notably, all the studies that I have cited thus far emphasize written products and
infer process information based on those products. Two other studies, one empirical and one
based on an analysis of forty textbooks, emphasize how readers process and respond to
written proposals. The first study, by Dycus (1977), is generally problematic in that its’
findings contradict much of what we have come to understand about the positive affects of
good document design on reader response (Duffy, Higgins, Mehlenbacher, Cochran,
Wallace, Hill, Haugen, McCaffrey, Burnett, Sloane, & Smith, 1989). That is, Dycus (1977)
42
found that proposal appearance had no significant affect on reader response. He explains
that “After continued reading, the evaluator’s impression of the proposal is based almost
entirely on the thought content of the proposal. At this point, any initial effects of
appearance on impression are almost completely washed out” (291). Improved proposal
appearance, in Dycus’ (1977) words, is “brochure-manship” or “cosmetics.” Numerous
researchers, however, have argued convincingly that attempts to separate the form of a
document from its function are generally problematic (Coe, 1987; Miller, 1984). Dycus’
(1977) stance that the “thought content” of a written proposal can be separated from the
manner within which that content is presented is, therefore, questionable.
The second study, by Freed and Roberts (1989), is a text-based analysis of forty
technical and professional writing textbooks. Disturbingly, their conclusions are that
“little disciplinary agreement exists about what proposals are and how they differ from
some kinds of reports” and that the textbooks “present a bewildering array of classification
systems, often failing to distinguish between situation and function” (317). Finally, they
suggest a view towards proposals, based on schema theory, as event sequences containing
multiple slots for information. This perspective, they assert, should help educators and
writers better understand the proposal genre and function (although they provide no
empirical evidence to support this claim).
The above studies of proposals have several things in common. First, none of them
document the actual proposal-writing process as it occurs in the classroom, laboratory (see
Chapter 3), or workplace (see Chapters 4 and 5). Second, they emphasize the text features
of written proposals out of the context within which they were produced. And third, they
offer pedagogic advice based on anecdotal evidence.
43
At this point, I turn to two studies—one of scientific journal writing and one of
scientific proposal writing—that have significantly informed the direction and design of
the proposal-writing study described in Chapters 4 and 5. The first study, by Jone Rymer
(1988), focuses on how eminent scientists write scientific journal articles. Her selection
criteria for the scientists she studied included “prestigious publication records, high
citation indexes, and extensive [experience] training graduate students” (215). Similar to
my study of proposal writing, Rymer’s scientists defined themselves as “biochemists,
enzymologists, or molecular biologists” (216). Her data are impressive and consist of “17
composing sessions (spanning 3 1/2 months)” as well as notes from seven of the composing
sessions (224).
Among her more notable findings, Rymer states that Scientist-Subject J treated his
“writing [as] a focal point for thinking about the research and making sense of the results,
[for] determining what the science all means” (228). That is, not only does scientific
writing act as a heuristic for discovery, but it also significantly influences the scientific
research being carried out; as Rymer notes,
. . . the planning of the paper is really part of the process of
structuring the research. . . . The research is being done to reach a
purpose. . . . Therefore, the intent to publish a paper is there before
the research (235).
According to Rymer, her study “shows that scientists are tellers of tales, creative
writers who make meaning and who choose the ways they go about doing so” (244). Of
Subject J’s writing process, she makes the following observations: (1) “Drafting/Revising is
a fused function, the focal point of J’s writing procedures” (232); (2) “Working from the
inside out characterizes J’s drafting process” (233); and, (3) “Overall revision after drafting
is a significant function in J’s process” (235). These findings, it should be noted, conflict
44
with the findings of Broadhead and Freed (1986) and Selzer (1983) who observed that
nonacademic writers rarely revise and tend to compose in a very linear fashion.
Finally, it is useful to contrast my research interests with those of Rymer.
Characterizing one scientist’s composing process, Rymer writes “In carrying out his tasks,
he typifies the behavior of his colleagues (for example, writing longhand on legal pads
[and] submitting drafts for typing section by section)” (221-222); because I was interested in
studying contemporary science “in the trenches” (rather than the writing processes of
“eminent” scientists), my subject was a young, untenured faculty member (see Chapters 4 and
5). And, since my scientist-subject operated in a highly competitive department, it was not
unusual for graduate students and young faculty members to aggressively seek funding for
research and equipment grants.15 The scientist I studied, therefore, did all his composing
on a microcomputer; moreover, his machine was linked to various library and abstract
services. Access to technology that supported his writing and reading processes, not
surprisingly, influenced the nature of those activities. In addition, Rymer explains that
most of her scientists “simply treat[ed] [student] drafts as raw materials to create their own
papers in their own style” (222). In this respect, as well, the scientist I studied controlled
the writing of his proposal from the outset, often incorporating the experimental data
produced by his graduate students and colleagues. Finally, Rymer’s (1988) study focussed
on journal-article writing, the genre which, as I have argued earlier, most rhetoricians and
sociologists of science have privileged (e.g., Bazerman, 1988; Gragson & Selzer, 1990; Gross,
15
As Mukerji (1989) has correctly pointed out, “It is conventional in analyzing the
role of science in modern societies to study well-established physicists or
biologists (i.e., elite members of traditional and prestigious sciences), and use
them as models for the rest of science, even though they are exceptional cases”
(14).
45
1985, 1990a, 1990b; Harmon, 1989; Popken, 1988; Swales, 1984; Swales & Najjar, 1987;
Zappen, 1985).
The second (1985b) study, this one focusing on proposal writing in biology, is
contained in Greg Myers’ (1990) compilation of previously published articles and represents
an impressive contribution to the field. Like Bazerman (1988, 1991), Myers’ method of
analysis is based in traditional literary analysis. Citing Culler’s (1968) article, “The
Darwinian Revolution and Literary Form,” Myers points out how significantly the work
influenced his research: “[Culler] identifies texts with the authors as represented in the
text, and imputes to these authorial personae various intentions and interests. In all this,
Culler’s article exemplifies the procedures I will be following in this book” (10). While I
agree with Myers’ motivation to study in detail the texts of scientific and technical
writers, the problem with such analyses is that—in privileging texts rather than the
processes of the scientists who produce them—we can only infer intentionality at best.
Similar to Rymer (1988), Myers (1990) establishes that research, data, and
scientific proposals for research funding are interdependent. Of scientific writing, Myers
contends “a text on a phenomenon takes on the same shape as that phenomenon, or rather,
the phenomenon takes shape through the text” (26). However, while he does discuss the
relationship between proposal writing and scientific research, he does so only generally.
Writing about the composing process of one biologist, for example, Myers (1990) asserts that
“Since he must discuss the alternatives to his model, he becomes more involved with
structure-function relations, if only to dismiss their influence here, so the context of his
research is changed by the process of applying for funding” (56). This interaction, Myers
(1990) contends, is not simply a matter of finding the appropriate expressions to capture the
46
“meaning” of the experiment: “Finding conventional terms for unconventional research is
not just an exercise in rhetoric—it changes the research” (60).
Whereas Rymer focussed on the interaction between drafting and revising, Myers
(1990) emphasizes the types of revising that the biologists engaged in. His conclusions are
that they revised three ways—for “changes . . . improving the readability, defining the
relation to the discipline, and modifying the persona” (47). Although he is not specific
about what form such changes took, his findings regarding revising for an academic
audience are supported by numerous other studies (Atlas, 1979; Bazerman, 1984; Campbell,
1975; Kaufer & Geisler, 1989; Mulkay & Gilbert, 1984).
Finally, both studies are, to my knowledge, the only two thorough analyses of the
writing processes (in the case of Rymer, 1988) and written products (in the case of Myers,
1990) of practicing scientists. Myers’ (1990) points to the gap I am interested in filling
when he writes, “I particularly need data from other disciplines and earlier and later
stages of the publication process, about how persuasion is planned before a draft is written.
. . .” (99). Methodologically, I am influenced by Rymer’s (1988) focus on the writing process
(data collected through protocols and open-ended interviews) and by Myers’ (1990)
emphasis on written products and on close readings of scientific texts. Both studies, I
believe, contribute important information about discourse production in the sciences,
information I am interested in extending with the studies described in Chapters 3, 4, and 5.
General Conclusions
I began this chapter by characterizing scientific proposal writers and reviewing
relevant literature from cognitive psychology, organizational behavior, and the sociology
of science. While these literatures provided us with various, related perspectives towards
47
science and scientific behavior, they all tended to de-emphasize the role of the scientific
research proposal and its relationship with journal-article publishing and scientific
research activities. This allowed me to describe contemporary research aimed as
contributing to our understanding of the following: (1) on viewing writing as both a social
and a cognitive activity; (2) on exploring the relationship between writing processes and
written products; and; (3) on uncovering the relationship between descriptive studies of
writing and prescriptive goals for instruction. Finally, I reviewed existing research on
proposal writing, in particular, focussing on the work of Rymer and Myers.
In the next chapter, I present two pilot studies of proposal writing and research
funding. The first is a talk-aloud protocol study of fifteen professional and technical
writing students producing short research proposals. The second is an interview-based
survey of fifteen academic researchers and emphasizes the contextual aspects of the
research funding process. I conclude by examining the strengths and weaknesses of each
study, and suggest that a long-term, detailed study of an academic proposal writer, in
context (see Chapters 4 and 5), will address many of the shortcomings of the two pilot
studies.
48
Chapter 3—Two Pilot Studies of Scientific Proposal Writing
What he wrote
What he meant
It has long been known that . . .
the
I haven’t bothered to look up
reference.
While it has not been possible to provide
out, definite answers to these questions . . .
a
The experiment didn’t work
but I figured I could at least get
publication out of it.
Three samples were chosen for detailed
study . . .
The results on the others didn’t
make sense and were ignored.
Accidentally strained during mounting . . .
Dropped on the floor.
Handled with extreme care throughout the
experiment . . .
Not dropped on the floor.
Agreement with the predicted curve is:
Excellent
Good
Satisfactory
Fair
Correct within an order of magnitude . . .
Fair
Poor
Doubtful
Imaginary
Wrong.
It is suggested that . . . it is believed
that . . . it appears that . . .
I think.
It is generally believed that . . .
A couple of other guys think so
too.
The most reliable results are those
obtained by Jones . . .
He was my graduate student.
Fascinating work . . .
Work by a member of our group.
Of doubtful significance . . .
Work by someone else.
Gilbert, G. N. & Mulkay, M. (1984). Opening Pandora’s Box: A Sociological
Analysis of Scientists’ Discourse. Cambridge, England: Cambridge UP, 176177.
49
This excerpt introduces an issue of particular relevance to this chapter’s content
and organization. That is, although I undertook both pilot studies with the best of
intentions, I was also aware of several potential shortcomings of both studies from the
outset. For this reason, I conclude the chapter by discussing some of the limitations of each
study in the light of what we do and do not know about scientific proposal writing in
anticipation of my third, and major, study of the genre.
A Talk-Aloud Study of Research Proposal Writing
The Participants
The participants for my exploratory study were 15 technical and professional
writing majors (six senior undergraduate and nine graduate students) enrolled in a
“Computers and Writing” course. All 15 students had written research proposals prior to
taking the course—either as part of another course or as part of an internship. Two out of
the 15 students had proposal writing as part of their job descriptions in previous work
experiences.
The Task
As the first assignment for the course, I asked the students to write a short (2 page)
proposal for a research project designed to inform some aspect of document design. To help
them select an appropriate research question, they were asked to refer to the research
agenda outlined in Schriver’s (1989a) article, “Document Design from 1980 to 1989:
Challenges That Remain” (see Appendix A). The students were told that most effective
proposals include the following generic information: (1) the project’s participants, that is,
50
who will participate in the study, how many will participate, how they will be selected,
and other major demographic characteristics (e.g., age, sex, etc.); (2) the materials used in
the study, that is, laboratory equipment used, its description, etc., and; (3) the methods
used in the study, that is, what you would do and how you would do it (summarize each
step).
Finally, students were instructed to pair off into groups of two and to take protocols
of their partners for 30 to 40 minutes while they wrote their proposals. They were given
instructions on how to do a talk-aloud protocol (see Appendix B). My goals for using the
talk-aloud protocol method were to explore; that is, I was interested in generating a series
of research questions about proposal writing, rather than in confirming any hypotheses
about the nature of proposal writing.
Seven out of the 15 students chose to study the differences between expert and
novice audiences and the role of subject-matter knowledge in reading, probably because
that topic had been the focus of a previous lecture. Six students proposed projects on various
issues such as the difference between oral and written communication, social factors
affecting document design, and the effect of visual design on reading comprehension. Two
students chose related questions on interface design.
Classifying the Protocols
I classified statements in the 15 think-aloud protocols into protocol segments (or
idea units) according to the approach used by Hayes and Flower (1980) and Burtis,
Bereiter, Scardamalia, and Tetroe (1983). Each protocol was then coded according to the
following categories:
51
(1)
Perc. Aud.—references to the writer’s perceived audience (i.e., to the
audience that would be reading and responding to the written proposal);
(2)
Prot. Aud.—references to the writer’s audience for the protocol (whether
the actual observer or the person who would ultimately analyze the
protocol);
(3)
Linear Org .—linear organizational comments (i.e., comments that
indicated the writer was following a linear writing strategy);
(4)
Non-Linear Org .—non-linear organizational comments (i.e., comments that
indicated the writer was not following a linear writing strategy); and,
(5)
Tone—references to the tone or “sound” of the proposal.
Two of the fifteen protocol transcripts were rated by two raters, to insure
reliability, and then five more transcripts were rated independently, achieving a
reliability rating of 83 percent. The remaining eight protocols were then coded by one of
the two raters.
Since I was also very interested in how the protocol data-collection technique
influenced the task and the writing process, I also coded for three types of “difficulties”
experienced by the participants during their talk-aloud sessions: (a) talk-aloud problems,
that is, references to difficulties experienced talking aloud and thinking or writing; (b)
technical problems, that is, problems with the word processing technology (the writers
were asked to compose using a computer); and, (c) laboratory problems, that is, comments
referring to the artificiality of the task being asked of them.
52
Issues That Emerged from the First Pilot Study
As discussed in the last section, three major interests driving my pilot talk-aloud
study were how professional writers their proposal’s audience, how they organize the
proposal-writing process, and how considerations of tone affect their writing process.
Partic. #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Ave
Idea
Units
178
306
175
102
152
146
138
173
113
181
145
156
95
147
241
163
Perc’d
Audience
0
0
0
0
0
0
0
11
0
0
0
5
0
0
0
1%
Prot.
Audience
6
8
3
0
0
1
0
8
0
2
3
0
3
3
13
3%
Linear
Org.
7
10
5
13
22
5
8
5
2
9
2
6
3
11
17
10%
NonLinear
Org.
0
10
0
1
3
0
0
7
1
0
7
0
0
0
0
2%
Total
#
Total %
Tone
3
5
0
0
0
0
0
3
1
0
2
2
1
0
1
1%
16
33
8
14
25
6
8
34
4
11
14
13
7
14
31
16
9%
11%
5%
14%
17%
4%
6%
20%
4%
4%
10%
8%
8%
10%
13%
10%
Table 1: The frequency with which the 15 professional writers considered the audience
(perceived versus the audience for the protocol), organization (linearly versus nonlinearly), or tone of their proposals.
Table 1 reports the frequencies with which each of these categories occurred based on the
mean scores of two independent raters.16
16
The headings for Table 1 have been reduced to save space. Briefly, they are as
follows: “Partic. #” is the # of the participant and his or her data summary; “Idea
Units” are the total # of idea units contained in each transcript; “Perc’d Audience”
is the # of references to the perceived audience for the proposal; “Prot. Audience”
is the # of references to the audience for the protocol transcript; “Linear Org.” is
the # of references to following a linear organization—from participants to
methods to conclusions, and so on—in the transcript; “Non-Linear Org.” is the #
of references to following a non-linear organization, i.e., from methods back to the
introduction down to the conclusion, and so on; “Tone” is the # of references to
53
The 15 protocol transcripts contained an average of 163 idea units each, ranging
from 95 to 306. Considerations of audience, tone, and organization took up only 10 percent of
the 15 protocols, while the majority of the protocols consisted of re-reading the written
text and task instructions, sentence level transcription, and sentence level evaluation and
revision. In the next three sections, I review the data in more detail and give examples of
each of the five categories.
Defining an Audience for the Research Proposal
The majority of protocol studies examining the way writers compose have
emphasized planning, transcribing, revising, and evaluation (e.g., Bereiter &
Scardamalia, 1987; Gregg & Steinberg, 1980; Hayes, 1989; Hayes & Flower, 1980; Hayes,
Flower, Schriver, Stratman, & Carey, 1987). Few researchers, however, have attempted
to track how writers construct or represent their perceived audience (cf., Atlas, 1979, Ede &
Lunsford, 1984, Petraglia, Flower, & Higgins, in press, for notable exceptions).
Indeed, the analysis of my 15 protocol transcripts revealed a limited number of
references to the anticipated audience for the proposals; only two of the 15 writers
(participants 8 and 12) directly addressed the audience for their proposal. Ironically, in
addressing their perceived audiences, both students highlighted the fact that they were
producing their proposals out of any meaningful context for production. One student, for
example, defined her audience generally as “the English Department” and then limited it
to the course instructor:
. . . who should I say it’s submitted to, should I say it’s submitted to the
English Department or Brad, ummm, is submitted to Carnegie Mellon
the sound or tone of the written proposal; “Total #” is the # of idea units (out of
the total idea units for the protocol) devoted to all five categories, and; “Total %”
is the total percentage of idea units out of the entire protocol transcript.
54
English Department . . . um, Brad, Bradley? No, Mehlenbacher,
instructor, computers and writing (Participant 12).
The second student made an explicit reference to the importance of defining one’s audience
and then, given the nature of the proposal assignment that he had been given, created an
“imaginary” audience for his proposal:
All right, okay, I’m writing a proposal, a short proposal for, okay, well,
okay, who the hell is this proposal going to? I mean, who am I supposed
to be writing for? Am I supposed to be asking for money, or what? Is this
a thesis proposal? I mean, the first thing a writer’s supposed to do is
think about your audience. It doesn’t say a research prop—oh yeah, it
does. Research project, okay. Uh, I’ll assume it’s for a research project
such as the Kellogg project, yeah, the Kellogg project (Participant 8).
His statement is particularly ironic in that his awareness of what it means to be “a
good writer” is at odds with the nature of the task he has been given; that is, the research
proposal task ignores the crucial role that context and audience awareness play in the
composing process.17 This confusion about the general audience for their proposal was
reinforced by the fact that 10 out of the 15 students referred, not to the audience they
believed would be reading their finished proposal, but to the audience of the protocol tape
itself. This tendency to address the audience for the talk-aloud protocol, in general, took
three forms: students either apologized for the way they were carrying out the task, or
interacted with the observer taping them, or censored comments that they felt were
inappropriate for the protocol audience.
17
It might be argued that the lack of reference, on the part of the participants, to the
context or audience for their proposals is an artifact of my particular task
instructions; i.e., had I stressed a plausible context and audience for the written
proposal in the instructions, I might have evoked more participant references to
such issues. I would maintain, however, that any set of task instructions creates
the possibility of emphasizing or de-emphasizing the participants’ problem
representations and problem-solving behaviors (cf., Simon & Hayes, 1974;
Simon, 1979).
55
Apologies tended to center around how the subjects were performing the writing
task, for example,
This is not what my paper is going to read like. I am just writing as I
think so I don’t forget anything I said. This isn’t what it’s going to look
like, I promise, because this is really, really ugly (Participant 1).
This is just an outline which is why I am completely grammatically
mixed up here; don’t worry about the way these sentences go (Participant
6).
One student revealed an almost painful dedication to carrying out the task properly for the
audience of the protocol:
Mmm, my contact lenses. I have a problem here. I’ve gotta stop. I swear
I won’t think about anything while I’m taking out my lenses, but I really
truly have to take them out. [Tape interrupted]. I’m back, my glasses are
on, my eyes don’t hurt anymore, I haven’t thought about anything, and
I’ll get back to what I was doing which was beginning to write out about
my rough draft on methods (Participant 15).
Interactions with the observer (the person in the room taping the student as he or
she wrote) or with the assumed audience of the protocol were usually either explanatory in
nature (i.e., I am currently performing this action for these reasons, etc.) or conversational
in nature (i.e., am I doing all right? etc.). The following are representative of such cases:
Fine, all right, how we doing on the tape? (Participant 2).
All right, am I doing good? (Participant 8).
For example, comma, ummm, where am I? For example a technical
writer—oops, spelled technical wrong, backspace to the accidental x—a
technical writer documenting a familiar word-processing package
parenthesis, for example, having used it for six months parenthesis may
focus on the high-power functions. [To the observer]: It’s probably
driving you crazy when I make mistakes that I don’t notice [laughs]
(Participant 14).
At this point, it’s twenty after seven. I’ve been working on this since
almost six-thirty, so it’s about forty-five minutes, which is what you
wanted (Participant 15).
56
And finally, their awareness of the observer caused some students to monitor comments
they felt were inappropriate:
Okay, I guess I will just go back and start to re-write this since my typing
is so bad, although this is going to be really boring to listen to. Are you
listening anyone? It’s boring (Participant 1).
Okay, umm, the subjects have to be college age, because then that way
you’ll get, no, they’ll pretty much all have the same ability, well, not
necessarily, some people are stupid. Take that back, I didn’t say that,
umm, they’ll be college age, male and female (Participant 11).
Three of the 15 students continually turned to the observer and asked “how am I
doing?” during their writing sessions. This tendency raises questions of observer intrusion,
an issue that clearly has no easy solution. That is, the alternative approach would be to
have the writers take protocols of themselves, which would remove the distracting
observer from the setting, but would introduce the possibility of them falling silent instead
of talking aloud continually.
Approaching and Organizing the Research Proposal
The findings in terms of how the 15 writers approached and organized the writing
of their research proposals were as follows. Nine out of the 15 students organized their
proposal and writing process following the linear formula set out by the task
instructions—introduction, followed by subjects, followed by materials, and so on. The
majority of the students (12 out of the 15) did little or no re-reading until they had
completed an entire section or paragraph of their proposal. Clearly, they viewed their
main goal to be to brainstorm the assignment and, therefore, spent very little time rewriting or revising, as is the case with the following two students:
57
Okay, I’ll want to come back and, I’ll definitely want to come back and
edit this paragraph, but I think I’ll just keep going mainstream, or
thought process, so that I’ll get what I’m thinking down (Participant 5).
The purpose, the purpose of this proposal is, I don’t know, I’ll think of
the exact words later. For this I’ll use an asterisk to denote that I cannot
think of the exact wording, but it is more important to get the ideas down
first (Participant 8).
This behavior—writing as a brainstorming activity—appeared to be unnatural for some
students. As one student commented,
Okay, ummm, hmm, I feel like I have to re-read part of this before I go
on, so let’s take a look at what I have here. Hmm, I am getting a little
antsy because I know I have a lot of editing and re-wording to do, and I
want to re-organize some of this stuff, but, I’m going to keep typing just to
get as much down as I can (Participant 5).
Only three of the 15 students deviated from the assignment’s outline significantly
(i.e., they made as many references to altering the established outline for the proposal as
they did references to following the set outline). In some cases, exceptions to the formula
set out by the task instructions took the form of simply renaming section headings, as in the
following protocol excerpt:
All right, so instead of subjects, I think the first heading I want to have
is . . . how about test groups, test groups, all right (Participant 2).
In another case, the student was obviously more comfortable working on any section of the
proposal she felt required more definition:
What else do we need to write down here? I need to explain my methods,
so I need to go back. I’m going back to the beginning of my document and
I’m going to go in after I write the question and, before I tell what I’m
going to do, I’m going to write methods, my method. And there’s
something else I think I want to call this, procedures section (Participant
11).
58
Unfortunately, however, the majority of the protocol transcripts (again, 12 out of
the 15) demonstrated the importance of lower-level text transcription rather than higherlevel organizational concerns. Hence the following student:
Because the level of expertise is subjective, the subjects—that’s really
good, subjective subjects—will consist of daily, occasional, oops, and new
users to ensure that the re—ooo, misspelled, control i to insert one little
letter—and break, seems like a lot of work—to oopsy, to ensurb to
ensure—now we have to do that control delete thing—no, then we’ll
have to do that control insert—to ensure that the research results are not
skewed—great word, skewed—skewed, skewed, skewed, by the use, uh,
oh, of a word processing program or hardware platform that may be
either easier or more difficult to learn and use than average comma.
Hmmm, I’ve got a lot of fixin’ here. Four different—oh—four different
programs will be tested on two different platforms (Participant 3).
Certainly, several interesting things are going on in this last excerpt. First, it
reveals the complex interaction between multiple goals for writing. That is, the student is
operating at numerous levels attempting, not only to transcribe the single sentence, but also
to brainstorm his overall research plan. These two goals, in turn, are confounded by
insignificant activities to which he must attend (at least insignificant given his goal of
producing a complete and coherent proposal), for example, word-processor-related
operations.
Constructing a Professional Ethos
Eight of the 15 students clearly recognized the importance of creating a
professional tone or ethos in their proposals. However, because they tended to view the
task as a brainstorming activity, they often drafted using colloquial expressions and made
mental notes to revise later, as the following excerpts exemplify:
When I write this up, a little note to myself, use references like subject
one and subject [laugh] . . . wonderful . . . two (Participant 1).
59
[The author I am referring to] champions the old-fashioned pick-anumber menuing system, in which the user is presented with a simple
numbered list. All right, simple’s kind of prejudicial there, so I’m just
going to nuke simple (Participant 2).
Two students made explicit references to the importance of “sounding” professional:
Now I hope to devise the reading comprehension test, and that reading
comprehension test should test for . . . speed it should test for. Oh heck, I
don’t know, how about subject satisfaction, and if they get upset they
aren’t going to learn anything, right? And all the other user-friendly
things, and all the other user-friendly criteria, okay, that’s real
professional [italics added] (Participant 11).
Okay, subjects, okay. I will advertise. . . . Actually, I’m not going to do
this in the first person because it doesn’t sound very professional [italics
added]. An advertisement will be posted, an advertisement will be
placed in the [school newspaper] asking for volunteers to do an
experiment (Participant 15).
All in all, the students’ references to the tone of their proposals tended to be
relatively superficial in nature. That is, not surprisingly given the assigned nature of the
task, their statements regarding the tone or sound of their proposals were often very
general (e.g., using the “royal we” instead of a personal pronoun, replacing colloquialisms
with formal expressions, and so on). In the next section, I explicate some possible reasons
for the lack of references in the 15 protocols to audience, global organization, and tone or
ethos construction.
Focusing on the “Noise” that Enters Protocol Data
As mentioned earlier, I was also motivated to track how the talk-aloud technique
influenced the 15 writers’ task orientations and writing processes. Certainly, my interest in
examining the “noise” in my data was, in part, political. That is, I was well aware of the
on-going debate between researchers interested in generating hypotheses about composing
60
processes from protocol data and researchers who criticize the protocol methodology. By
looking at where the technique intruded or altered how the 15 students appropriated the
writing task, my intention was to highlight—not only what protocols can do for us—but
also what protocols cannot do for us. To this end, my co-rater and I coded for three types of
recurrent “technical” difficulties:
(a)
references to difficulties experienced talking aloud and thinking or
writing;
(b)
references to problems experienced with the word processing technology
(the writers were expected to compose using a computer); and,
(c)
references to the setting within which the writers were asked to compose.
Table 2 shows the frequency with which such references occurred across the 15 protocol
transcripts:
Participant #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total
Problems
Talking Aloud
0
0
0
0
0
2
0
0
0
0
0
0
3
0
0
5
Problems with
Technology
0
2
44
2
0
0
5
2
1
4
0
2
0
1
0
63
Problems with
Context
2
0
0
0
0
1
0
5
0
9
0
0
0
0
0
17
Table 2: The frequency of “technical” difficulties reported by the 15 professional writers.
61
Only two of the 15 students made explicit references to difficulties that they were
having trying to write or think and talk-aloud simultaneously:
It’s hard to talk and type at the same time. It’s really difficult
(Participant 6).
[Observer]: What are you thinking?
[Participant]: I don’t know. I’m trying to think. And I can’t think outloud.
[Observer]: You’re supposed to think out-loud. It’s a think-aloud
protocol.
[Participant]: I’m sorry, it’s my first think-aloud protocol (Participant
13).
Nine out of the 15 students had significant technical difficulties including
problems using their computer mice (Participants 7, 9, and 12), difficulties with their
keyboards (Participants 4 and 10), trouble saving their documents (Participants 3 and 5),
difficulties formatting their documents (Participants 5 and 7), and problems with their
computer monitors (Participant 8). Participant 3 had the most significant difficulties,
probably because of her unfamiliarity with the computer software she used to create the
document. Although the interaction between technological medium and the composing
process was not the focus of my research, the intrusion of the word-processing software on
the writing process certainly represents an important factor that requires future
investigation (cf., Duffy, Palmer, & Mehlenbacher, 1992; Hill, Wallace, & Haas, in
press).
Finally, we coded for any references that implied that students found the task
situation artificial or “unreal.” Only four out of the 15 protocol transcripts contained
explicit comments about the nature of the task. Observe the following participantobserver interaction:
[Participant]: Am I doing the protocol right now?
[Observer]: Yes, we’ve been doing the protocol since you started talking.
62
[Participant]: Okay, here I go, I’m doing a protocol. I’m calling up, in
Word, a new document. And there it is. I’m sitting in front and I’m
starting timing. We only do this for half an hour. It’s 8:06 and thirty
seconds. Okay, so approximately 9:35, er, yeah, 9:35. . . . All right, here
I go. I’m beginning my assignment. First I gotta figure out what my
assignment is. My assignment, I already read. Okay, my proposal is
going to be on—hey, that little red light blinked [pointing at the taperecorder].
[Observer]: It’s supposed to blink.
[Participant]: Why did it, oh, it blinks when I talk. Wheeoooh,
wheeoooh. Hey, that’s pretty cool (Participant 8).
One student, after finishing his proposal, described the writing and the proposed research
as “pretend,” and was disappointed because, during the production of the proposal, he had
developed a vested interest in the subject matter:
I’m sorry this is pretend now because I am kind of psyched. I kind of want
to do this. Of course, I could not go to Japan and talk to these people, but I
guess I’d get someone to interpret for me. And that brings in so much more
(Participant 1).
One student explicitly described how her “normal” writing activities differed from
that of the protocol session. The most important factor confounding her session turned out to
be her need “to do more research” on the subject she was writing about:
Okay, well, I think I’ve basically covered all of the beginning options
and now what I would begin to do is I would move off the word-processor
at this point and go onto pen and paper, and start to do some research on
this. Since these were my initial thoughts and I came up with the
subjects and the materials and the methods.
[Later].
Okay, one thing, I just went and got the hardcopy and this is the first
time I’ve ever sat down with the word-processor from scratch and put my
ideas on the computer. I normally start by pen and paper and doing an
outline and sitting down and doing all the research necessary. It’s
usually a little more organized than this. This was a little more freeflowing than I usually do it, but it did give me the basic ideas, I think,
from where I would proceed (Participant 10).
63
In general, my data suggest that thinking aloud influences the composing process
for at least some writers, although we do not know exactly what that influence means for
researchers studying the process. In addition, it is interesting to note that the technology
used to create the proposals had more of an influence on the writing process of the 15
technical and professional writing students than the think-aloud protocol method.
General Conclusions
To anyone who has watched or listened to writers talking aloud while they
compose, many of these observations may seem at once obvious and secondary to what the
protocol data do tell us about the composing process. My point here, however, is that if
they are so obvious, then it is surprising that so few researchers have addressed the
implications (see Ericsson & Simon, 1980, 1984, and Steinberg, 1986, for notable exceptions).
Most importantly, the above excerpts point to the problematic nature of giving writers
artificial writing tasks. A great many of the negative comments about their writing
experience revealed that they were frustrated by their inability to truly appropriate the
writing task. This frustration was due, in part, to the staged quality of the task itself, to
the lack of a “true” audience for their proposal, and to the lack of a meaningful context for
writing (other than the laboratory context in which they found themselves).
Before turning to the second exploratory study, it is important to return
momentarily to Bazerman’s (1988) description of the proposal-writing process and to the
many questions about proposal writing that, as yet, remain unanswered (see Chapter 1).
While the talk-aloud protocols told us numerous important things about the writing
process—for example, the degree to which issues of audience and tone influence the
students’ writing activities—they told us very little about the various types of negotiation
64
that Bazerman cites as critical. For example, we learned little about the relationship
between scientific and technical research and the proposal-writing process. Because they
involved a laboratory context for writing, and not the actual setting within which
professional writing occurs, we gained little information about the scientific and technical
settings where proposals are generated, read, and evaluated. And, finally, because the
protocols were of single writers producing texts in isolation, we learned little about the role
of collaboration and negotiation that takes place between scientific and technical writers
and their peers, funders, and discourse communities in general.
Bringing Context into the Study of Proposal Writing
The Participants
I conducted the first study to establish some working hypotheses about the
proposal-writing process. A second, interview-based survey was aimed at uncovering
context-specific information about proposal writing and funding in the academy. Its data
consist of a series of open-ended interviews with 15 academic research scientists and
engineers from various disciplines including physics, cognitive psychology, mechanical
engineering, chemical engineering, and computer science.
The Open-ended Interviews
The open-ended interview questions focussed on the process of getting research
funding, perceptions about the differences between funding agencies and the academy, how
academic researchers communicate with research funding agencies and organizations, and
their research backgrounds and interests. Importantly, the second study emphasized the
65
processes surrounding proposal writing and funding activities, as well as the social and
contextual factors that constrain and enable the activity. Again, the study was
exploratory and only aimed at fleshing out some of the disciplinary, institutional, and
cultural constraints confronting academic proposal writers.
In the interviews, I focussed on eliciting information about the research scientist,
his or her research team, facilities and equipment, and perceptions of his or her research
field and agenda. The interviews lasted between one hour and an hour and a half (see
Appendix C for a representative list of the interview questions).
Issues That Emerged from the Second Pilot Study
The Organizational Politics of Proposal Funding
The first and most prevalent representation of the proposal writing and funding
process, by all 15 academic researchers, was that it is a highly political, multiinstitutional enterprise. One researcher, characterizing his personal funding experience,
describes how complex and enormous funding situations can sometimes be:
I think the proposal we had was a five year budget of about 15 million
dollars. We decided what we would do is we would attempt to build a
full-scale online library using today’s technology. And . . . they had, I
think, eight hundred proposals and they funded four and, in fact, it
turned out to be pure politics and they didn’t fund any in states where
there were already engineering centers, and since we had two engineering
centers in [this state], none of the science centers went into [it], which I
think was a pity because there were at least two other proposals from
[this university] which were really good.18
18
The term “political,” in this case, is used to describe the affect that a hidden
criterion (i.e., the geographical location deemed appropriate for new centers) had on
the research scientists’ ability to obtain funding from a particular funding agency.
66
The same researcher points out that his being a part of a large project is the result
of years of contacts that span numerous universities and corporations:
. . . when I was at University A, one of our star students introduced me to
his father who was, at that stage, working for ABC publishing company,
and his job was involved with electronic printing publishing. Some years
ago, after I was at University B, we wanted to get an online dictionary
for the computer system. . . . Knowing that ABC publishes dictionaries, I
called up this fellow . . . and said—to cut a long story short—it’s through
that contact that we came to the arrangement to put the ABC dictionary
online. About the time that the project was taking place, what we call
the Uranus Project, he transferred from ABC to GHI corporation, and got
involved in trying to set up a group in his area. We knew him already,
he was very keen to support our work, so it was a joint contact, which led
to us sending a proposal to GHI.
Also, as one might expect, given the complex and extensive types of negotiation
that are part of the funding process, the academic researchers referred to numerous
situational factors that constrained their ability to successfully obtain funding (e.g.,
yearly budget requirements, where specifically the money is located, etc.):
So it was a lot of people who have been working together in the same
areas, and that’s basically how we did it, and we spoke with our contact
and, you know, he visited here, we visited there. . . . He has to put up
some money from his budget and, being new to GHI corporation, he spent
some time trying to figure out what was the appropriate way to go about
things. We took his advice and we put in an equipment proposal, which
would have been last June because . . . they wanted it actually to get
funded from last year’s budget. . . . And they funded it partly from the
previous year and partly from this year. And that went through very
smoothly. . . . He has also funded some specific projects. He’s funded
some work by two researchers in computational linguistics. That’s not a
formal external research grant, that’s from his departmental provisional
budget.
In the above excerpt, for example, the researcher explains that numerous individuals
collaborated to make the funding situation a reality, that repeat visits were a part of the
process, and that—even though both sides of the negotiation were interested in pursuing a
67
research relationship—proper allocation of funds required intense and creative attention
from the interested funder.
And finally, one researcher talked at length about his experiences with what he
referred to as “experimental funding arrangements.” In one such case, for example, the NSF
refused to fund any proposals that did not provide evidence that the research scientists
could obtain their own, required equipment:
So part of our proposal process was, not only to propose to do the work, but
to line up promises of equipment from manufacturers. . . . This was kind of
a new idea for NSF. They were trying to leverage their money in the
sense that the head of NSF said, we’re not going to pay for equipment
anymore, we’re going to coerce the manufacturers to give it. So, in many
ways, when they first announced this proposal process, when they first
announced the fact that they were going to give these grants, there were
people from [four large corporations], they were all there too, even before
we submitted the proposals. So, ultimately, the way it works is we
prepare this proposal and talk with multiple companies about supplying
equipment for it, and they were going to supply the equipment—partly
for the people doing the software to use, but partly to put this equipment
in critical places in the universities. . . . And ABC corporation, out of all
the companies, . . . was extremely straightforward and supportive in the
way they handled this one. . . . And, in this particular case, it was
almost as if ABC corporation was saying, look, we’re going to support the
National Science Foundation, whoever the universities are who get the
money.
In conclusion, in more than half of the 15 academic researchers’ opinions, getting
proposals accepted had more to do with the political “talk” that took place between
researchers and (interested individuals within) funding agencies than it did with the
actual proposals that researchers eventually submitted for review. Certainly, this finding
confirms what other researchers interested in the funding process have suggested; as
Mukerji (1989) points out
If you look just at the proposals and research reports sent to agencies, it
looks as though the center of the communication system lies in scientists
writing documents for the government about their proposed and actual
projects, but that is not the whole story. Even more information is
68
gathered informally by scientists and agency personnel. Scientists use
their connections to figure out how to make their proposals as fundable as
possible (62).
This, of course, does not negate the importance of understanding how to produce an
effective proposal but, rather, points to the importance of incorporating oral
communication skills (e.g., the art of negotiation and fact-finding) into the teaching of
proposal writing. That is, proposals are never written in isolation, as students were asked
to do in my first study. Proposals are submitted and funded as part of a complex social
process. The next section discusses the interaction between proposals, funding, and the
research activities of the 15 academic researchers.
The Interaction Between Proposals, Funding, and Research
Proposals are not only intertextual in the sense that they borrow from and are
influenced by a broad corpus of scholarly research; they are also generated and regenerated across a series of corporate and government funding agencies. As one researcher
pointed out
Yeah, well the [boundaries between different sources of funding are]
fuzzy in the sense that, if one project is funding me ten percent, and
another project is funding me ten percent, and another ten percent, and
another one ten percent, I have ideas that transfer across all of them.
Okay, so where do I create an idea, you know. If I had this idea . . . that
could be used in a variety of places, I just list them all [the sources of
funding]. I can’t . . . I don’t write down every hour that I’m here, you
know, the three great ideas I had, and this hour was brought to you by
ABC funding agency and the makers of Stouffer’s frozen food.
Researchers differed on the ethics of receiving multiple sources of funding for their
research. One researcher, for example, felt that how much or little projects overlapped in
69
terms of the research results they produced was an issue that researchers needed to pay
special attention to:
What we would not do is enter into a relationship with a different
funding agency that focusses on the same kind of problem. We would tend
not to do that. Not that it’s illegal or anything like that, it’s just that . .
. sort of two things. One is it wouldn’t make ABC company very
happy—it’s not proprietary, we’re publishing this stuff—but also it
wouldn’t, it’s not clear what the benefit to us would be. It’s sort of easier
to work with one motivated partner than to sort of work with
competitors, each as partners. On the other hand, there are other
funding agencies that we do talk to and get funding from on very different
things. Right now we’re talking with some other companies about
potential funding for some other work. Quite different. The practical
effect of that would be very different from the practical effect of this,
and so it’s not really in any sense a conflict.
Along with expressing concerns about the audiences for different proposals and
different sorts of research, almost all of the 15 researchers emphasized the proposalwriting process as a process where achieving group consensus, effectively managing large
documents with multiple authors, and resolving conflicts between the proposal writers and
the intended audience for the proposal played key roles. Perhaps this explains why the
above researcher preferred working with “one motivated partner” rather than with
“competitors, each as partners;” that is, the single relationship allowed him to channel
his communication efforts with a single party and to focus on the research being carried out.
Another researcher characterized his experience writing a large proposal as follows:
Actually what happened, in this case, and this is fairly common, is that
one person will write a draft of the proposal. That is, we all sit around
in a room and talk about what ought to go in this proposal. Then we
make sort of a one-page outline—what are the key ideas, sections, and so
forth. And then one guy goes off and writes a draft of it. And it’s online.
And then somebody else will take a turn at going through that draft, and
just change anything they don’t like. Or, if they think that there’s a
serious conflict, then they’ll sort of go and argue it out or whatever. And
then it sort of cycles to the next person. And so it sort of gets iteratively
refined. And then, usually the person who wrote the first draft is the
first author on the proposal and really has the strongest statement of
how the proposal really turns out. Because the rest of the people just sort
70
of push it one way or another. But that’s really standard. The other
mode is that you say, you write this section, I’ll write this section, he’ll
write this section, then we’ll glue them together. That happens, but it’s
less common.
Although he does not indicate why one collaborative strategy is more common than
the other, the key is that the proposal-writing process described by the above researcher
is one where multiple writers negotiate with each other through a single document. And,
as stated earlier, this conception of proposal writing—as highly collaborative in
nature—has been generally ignored by most contemporary research on proposal writing
(e.g., Budish & Sandhusen, 1989; De Bakey, 1976; Freed, 1987; Freed & Roberts, 1989;
Mattice, 1984). In the next section, I discuss some of the researchers’ observations on an
equally important aspect of proposal writing and funding; that is, the differences they
described between dealing with different funding agencies and organizations.
Differences Between Funding Sources
Five of the researchers discussed their experiences in dealing with two different
types of funding groups. The first observation was that working with corporate funding
agencies and working with government funding agencies represented very distinct types of
interaction. As one researcher stated
. . . with ABC corporation we’re really working very directly, that is,
[our contact] is here every two weeks. . . . I mean, he is a participant in
this research project, so that’s very good. The higher bandwidth the
communication, the better off you are. There’s no doubt about that. Both
in terms of the company being aware of what’s going on, and getting
something out of it, and in terms of us understanding . . . the thing is that
we get something very important out of this relationship that we
wouldn’t get if we were funded by NSF or some government agency. And
that is, we get ABC company’s insight into what are the practical
problems that they face which, if we could come up with some
breakthrough, would really have an impact. . . . This way, since we’re so
tightly coupled, we really get something important out of that.
71
“Having an impact” and solving practical problems was very important to all 15
researchers, and this may be more a function of their disciplines (largely engineering and
computer science) or of the Carnegie Mellon environment. As one researcher pointed out,
Carnegie Mellon is largely a “federation of entrepreneurs.” In this respect, working with
corporate funding groups was described in a much more positive light than might have been
expected. Unfortunately, one researcher lamented, academic scientists are being forced to
turn increasingly to federal and other government agencies for funding:
So, it turns out that, even though maybe ten years ago there was a big
push to get money from industry, a just sort of movement within the
country to try to have. In fact, that hasn’t come about, anywhere near as
much as people were, some people were hoping it would. Including me.
Finally, some of the researchers (four out of the 15) expressed strong concerns that
our North American funding situation is problematic when compared to the habits of
foreign funding arrangements.19 They stressed the need for a process that strengthened the
interaction between them (as academic researchers) and other academic and nonacademic
researchers. One researcher told the following story:
. . . this year, in my research group, we have visiting researchers . . .
[from Japanese, British, and French corporations and government
agencies] come here as visiting researchers. The companies—they’re
employees of these companies—they come at the expense of the company
and spend a year or a year and a half here working on some kind of
research project that’s of interest to them, and us, and so what they get
out of it is some exposure to a lot of work going on here; what we get out of
it is some very bright people who will become full-time researchers for a
year or more, and who provide very important manpower and brainpower for getting our work done. And it’s a great arrangement. U.S.
companies seem to never do this . . . and it just strikes me as a real big
mistake. And I’ve talked about this with people from various U.S.
companies, but it’s a very strange situation, because when I tell them
19
Suzanne Roberts, of Applied Technology Associates, Inc., has correctly pointed
out that—despite the U.S.’s huge investment in research and development (more
than $100 billion in 1990)—”. . . the commercial return on our investment is
inadequate, particularly with regard to the lion’s share of this tab of about $30
billion sponsored by the federal government” (1991, 336).
72
that people are coming here from DEF, and last year we had people from
JKL and various Japanese companies—especially like to do this—then
the U.S. company people tend to get upset about that. They tend to say,
well, you know this is crazy, here’s the federal government and people
supporting U.S. universities, and people are coming in from other
countries and getting all the good ideas and then next year there’ll be
some product that comes out that markets this idea. Now, at the same
that they’re upset, for some reason, it doesn’t occur to them that they
could do the same thing, the fact that we would welcome them doing the
same thing.
The goal of the second pilot study was not to learn about the entire funding process
but, rather, to find out how academics interact and communicate with funding
organizations. All 15 researchers tended to see the actual research proposal as a very
small part of a much more important and on-going process (e.g., establishing what types of
political and social factors are influencing a funding agency’s interest in funding one branch
of research instead of another, etc.). This was not entirely surprising since the actual
written proposal is a integral part of an extended process designed to support meaningful
research in academic and nonacademic organizations. In the next section, therefore, I will
share some of the researchers’ discussions of the long-term implications of accomplishing
funding arrangements—particularly as it relates to transferring ideas, technology, and
processes into federal and corporate organizations.
The Continuum from Proposal Funding to Technology Transfer
The majority of the interviewed researchers (nine out of the 15) felt that, not only
was it important that communication between academic researchers and potential funding
groups be strengthened, but also that that communication be well-maintained over long
periods of time. The real concern, here, was that ideas and products would “get lost in the
shuffle” if such communication channels were not well-established. In the words of one
73
researcher regarding the minimal interaction between his research group and that of a
funding group:
It worries me, because I would actually like more of an interaction,
because I would feel more comfortable about the fact that they are
benefitting from [our research] and, therefore, will continue to support it.
And that’s the thing that concerns me. They don’t exercise their options
to interact with us as much as I’d like to see.
And, surprisingly, the researchers felt such failed attempts to move ideas and products out
of the academic context occurred both with federal and corporate relationships. As one
researcher observed about his interaction in one funding situation:
He [his contract monitor] drops by, it seems to me, two or three times a
year and asks how the research is going. He hasn’t explicitly asked me
about deliverables. This has been a fairly loose arrangement. I think
he’s come by with a bunch of people from the group, and they’ve asked
me what we were doing, and I gave them an oral report. And they can see
what we’re doing is approximately what we proposed to do.
Another researcher, describing what she felt had been a very successful funding
relationship, described problems that she had had with other corporations with which
she had worked:
What you quite often find at other companies is you’ll do a project which
the company sponsors but there’s nobody in the company really interested
in picking up the ideas. So what you do is you do a project which is your
own project and it’s financed by the National Science Foundation or
something like that, and the company loses the benefit.
The consensus among the researchers, therefore, seemed to be that—while working
with “real” (i.e., nonacademic) problems was very important to them—the difficulty with
interacting with corporate versus government funding groups was that corporate groups
tended not to “think long-term.” One researcher stated this explicitly and described how
some corporations are seeking federal support to overcome this shortcoming:
74
The only difficulty is that, dealing with, only with industry, . . . you
have a difficult time putting together one, coherent program that has a
long-term focus to it, because all the companies have different views of
how, what they’d like to see done and, therefore, you can’t put together
one nice, coherent program, without reasonably trying to get, and ABC
company as well as all our other sponsors have been helping us to get
support from the NSF for a long-term push, and then we would have a
more long-term push of both the support from ABC company as well as
the National Science Foundation.
Short-term thinking is not caused simply by the general structure of corporate
organizations. Another researcher identified what he felt was an even more major reason
for the problem:
. . . it always boils down to, there’s no one who has on his schedule
anything related to getting ideas from someone else. Nowhere in their
design and their development process is there a mechanism for
transferring technology. . . . And I don’t know why that’s true.
Referring to the same corporation, he added
ABC corporation has probably been the poorest at translating what we
do back into the company. And I think that’s because, again, there’s no
established conduit, there’s no way to get stuff back to them. If, by
accident, someone at ABC corporation happened to discover you’re doing
work and, by accident, they happened to discover it’s relevant to them
and, by accident, they happened to get it, that’s fine. And that
occasionally happened. It never happened to me personally, but I’m sure
it will happen to someone. . . . They don’t have in place even the
mechanisms for tracking what gets done in the universities, and trying
to—you know, I never had a guy from ABC corporation, never in my entire
life, come into my office and say, we would really like to get some of your
ideas into our system. It never happened, never ever happened.
Although this section focussed primarily on the outcome of research funding, and
not on the proposal-writing process itself, it did address some of the communicative aspects
of the process that Bazerman (1988) alluded to when he characterized needed proposalrelated research. In the next, and final section, I will discuss some of the issues the openended interviews did not raise.
75
General Conclusions
My second look at proposal writing and the funding process uses the retrospective
accounts of 15 academic researchers. Again, as with the first pilot study, my intention was
not to prove or disprove established hypotheses but, rather, to generate insights into the
proposal-writing process and its role in the larger, institutionalized funding process. This
second survey focussed on the organizational politics of proposal funding, and on the intense
interaction between written proposals, funding processes, and academic research.
Because the second survey relied on open-ended interviews for its data, I was
aware of the constructive nature of the information (cf., Gilbert & Mulkay, 1984; Odell,
Goswami, & Herrington, 1983). As Perkins (1981) has observed, “people really [have]
little access to their mental processes. Instead, people simply report . . . how they thought
they must have done something” (27). Or, as Brown and Canter (1985) warn, “events may
be reconstructed to answer questions that informants may not have conscious awareness of,
or provide an overview of an experience beyond the knowledge of any one participant”
(222). Despite these concerns, the data are still illuminating for several important reasons.
First, the 15 researchers point to the importance of oral communication in the overall
funding process, and they highlight the need for management and organizational skills to
an academic interested in getting research funding. Second, they establish the importance
of viewing proposal writing and research funding as a long-term endeavor, and not as
something that can be studied effectively in isolated writing incidents.
In describing their funding relationships, for example, the academic researchers
rarely limited their remarks to descriptions of the particular proposal documents that had
resulted in their being funded; rather, proposal writing and funding were one part of a
76
greater interaction that involved internal concerns (e.g., departmental- and college-level
as well as research-related) and external concerns (e.g., the number of funding
relationships available to them as well as the need to foster and maintain on-going
relationships). This highlights the difficult challenge that we, as writing researchers,
constantly face—the impossible goal of judging a given document’s effectiveness in the
light of external constraints which may make a well-written document fail or a poorlywritten one succeed (if obtaining funding defines success).
Implications of the Pilot Studies for Research on Proposals
Current developments in writing research have implications for the first pilot
study and for the survey of researchers. That is, contemporary researchers are interested in
expanding our current writer-centered, process-centered view towards writing to account for
the social dimensions of the communication act. Certainly, the debate between researchers
interested in writing as a cognitive activity versus writing as a social act is a wellestablished one (see, e.g., Bartholomae, 1985; Berlin, 1988; Bizzell, 1982a, 1982b; Bruffee,
1986; Flower, 1989). However, much of their debate has emphasized theoretical
perspectives and points of contention and ignored the fundamentally different approaches
they use to study the writing process.
For over ten years, for example, cognitive research on writing has benefitted
substantially from protocol studies of writers composing in isolation (e.g., Hayes & Flower,
1980), a methodological technique borrowed form cognitive psychology and computer
science (e.g., Card, Moran, & Newell, 1985; Ericsson & Simon, 1980, 1984; Newell & Simon,
1972). Recently, however, researchers have begun to question the effectiveness of protocol
data (e.g., Cooper & Holzman, 1983; Odell, Goswami, & Herrington, 1983). Cooper and
77
Odell (1976), for example, found that protocols of writers missed important information
such as the writer’s sense of audience and efforts to construct an effective ethos, and
changed depending on whether the task was experimental or “real-world.” My first pilot
protocol study, as well, highlights the need for studies of writers as they produce texts in
natural settings over extended periods of time.
And it is precisely because of this interest in documenting “real-world” settings,
that issues of methodology have re-emerged in the literature. Researchers interested in
studying the writing of academic professionals (e.g., Gragson & Selzer, 1990; Rymer, 1988;
Selzer, 1983; Winsor, 1989) and nonacademic practitioners (e.g., Anderson, Brockmann, &
Miller, 1983; Brown & Herndl, 1986; Harrison, 1987; Moran & Journet, 1985; Odell,
Goswami, & Herrington, 1983), therefore, have supplemented their data-collection
methods with methods borrowed from sociology, anthropology, and ethnomethodology. As
Doheny-Farina and Odell (1985) assert, “If researchers assume that they want to
understand the significance of a given action in a given social context, they will have to do
their research in a naturalistic rather than experimental setting” (506).
Applying this methodological perspective to a study of proposal writing, then,
necessitates that writing researchers enter the laboratories and offices of actual proposal
writers. In addition to collecting talk-aloud protocols of these writers as they compose
proposals for research funding, writing researchers also need to document (through openended, discourse-based interviews, and taped meetings) the departmental and
institutional constraints facing those proposal writers. These techniques, borrowed from
sociology and ethnography, should in turn provide writing researchers with a “thick
description” of proposal writing in a naturalistic setting (cf., Garfinkel, 1967; Geertz, 1973).
Finally, the problem with building a thick description of proposal writing is connected, of
78
course, with time and the density of the context in question—on-going laboratory
activities, journal-article writing, proposal production, evaluation, and implementation
are complex activities and usually take place over years and sometimes decades. Even
conducting a case study of one proposal writer, therefore, has turned out to be an enormous
task (see Chapters 4 and 5).
To summarize, in this chapter I described two pilot studies aimed at helping us
understand the proposal-writing process more fully. Although both studies provided us
with some interesting insights into the general nature of the proposal-writing process, I
concluded by outlining some of the shortcomings of both studies. Finally, I argued that a
naturalistic, long-term case study of scientific proposal writing in context would provide us
with data that both studies de-emphasized.
In the next chapter, I describe in detail the methods used to study a biochemical
engineer as he wrote proposals for research funding. Given the goal of describing proposal
writing as a complex process, while at the same time tying that process to the production of
a finished proposal, my major strategy has been to detail a “complete time record of the
production” (Britton, 1978) of one proposal written and submitted to the NIH. Also,
because a “complete” picture of proposal writing inevitably begins well before the writer
sits down at the terminal and begins writing (and extends well beyond the proposal’s
evaluation and possible acceptance), I collected data on the biochemical engineer’s
perceptions of his research agenda and its relation to the scientific and engineering
community in general, on his research-article writing, and on an unfinished proposal
written six months prior to the proposal under study. Much of my description of the
production of a single research proposal written for submission to the NIH, therefore, is
couched within the broader context of two years of on-going research and writing.
79
Chapter 4—A Case Study from Biochemical Engineering
It is a capital mistake to theorize before one has data.
Sir Arthur Conan Doyle, “Scandal in Bohemia.”
It is assumed that, in the long run, it will be possible to bring together the
conclusions of a number of such case studies to formulate a provisional, yet
empirically based, social theory of scientific knowledge-production or to
test and improve upon existing conjectures about this broad area of social
action (249).
Potter, J. & Mulkay, M. (1985). Scientists’ Interview Talk: Interviews as
a Technique for Revealing Participants’ Interpretative Practices. The
Research Interview: Uses and Approaches. M. Brenner, J. Brown, & D.
Canter (Eds.). NY, NY: Academic P, 247-271.
Then the control aspect. Oh yeah. Can’t have a wonderful technique
without controls on it.
First taped meeting of Raymond and Larry, the biochemical engineers.
As outlined in Chapters 1, 2, and 3, the major questions driving my study of how
scientists and engineers write research proposals for funding are:
(1)
How do scientists and engineers represent the perceived audience of their
research proposal; that is, how do they characterize the traits of their
intended audience? Do they refer to their audience’s research interests,
sub-specialties, background, biases, values, and so on?
(2)
How does the perceived audience for research proposals influence the
organization of the proposal, the content of the proposal, and the
80
presentation of the data reported in the proposal? That is, in the
planning, writing, revising, and evaluation stages of the proposal-writing
process, how frequently do scientists attempt to anticipate potential
audience problems or reactions to their document?
(3)
How does the proposal-writing process influence and alter data-collection
techniques and laboratory practices? Does writing a proposal affect the
manner in which scientists present and justify their research activities?
(4)
How frequently, and in what particular instances, do scientists incorporate
existing scientific research or literature in their proposals or research
plans?
(5)
How frequently do scientists discuss the numerous rhetorical alternatives
or strategies available to them in the proposal-writing process? How do
they adhere to the discourse conventions of their field while at the same
time attempting to represent their laboratory activities in an interesting
and novel way?
(6)
How, in general, is the proposal-writing effort managed over time; in
particular, what is the interaction between text and talk in science and
engineering?
These questions were informed, in part, by Bazerman’s (1988) and Myers’ (1990)
discussions of the role of writing in the sciences and, in part, by my experiences collecting
and analyzing the data described in the previous chapter. In particular, both Bazerman
and Myers point to the crucial role that scientists’ representations of the audiences for
81
their texts play in the construction and dissemination of scientific knowledge (see questions
1 and 2). The two pilot studies described in Chapter 3, while providing useful information
about the nature of proposal writing and funding in the academy, de-emphasized the
interaction between written discourse and scientific research activities (question 3), as well
as the inevitable interaction between new scientific texts and the body of existing texts
from which scientist-writers must draw (question 4). And finally, Bazerman and Myers
stressed the importance of examining how scientists come to make the choices they do when
writing and how those choices inform the texts they produce over extended periods of time
(questions 5 and 6).
In this chapter, therefore, I outline the sources of my data and describe my method
of coding and analysis. I begin by describing, briefly, the context within which I collected
my data. Next, I discuss an approach to data collection and design—called Participatory
Design—which influenced my on-going study of a biochemical engineer and his colleague.
Although the data I collected dates back to a writing project undertaken two years ago, the
emphasis of my analysis is on the most recent proposal-writing project (i.e., the three
writing projects I collected data on are presented in reverse chronological order starting
from the most recent and dating back to 1988). Finally, the three writing projects were as
follows: (1) the most recent collaborative proposal-writing project, (2) an earlier proposalwriting effort, and (3) a journal article written before the two proposal-writing projects
were undertaken.
Data Sources and Collection
The data that I collected to answer the above research questions span two years of
a biochemical engineer’s writing and research career. As with any long-term endeavor to
82
collect detailed information about a complex activity or process, my data represent a
myriad of information types. Most of my data were collected during an intense, three-week
writing period (from September 10th to October 1st, 1990) in which a biochemical engineer
(Raymond) and his colleague from a nearby university (Larry) collaborated on a proposal
for research funding that was ultimately submitted to NIH. The collaborative proposal
project was particularly interesting to me for several reasons:
(1)
the biochemical engineer and his colleague were working against a fixed
NIH deadline and, hence, drafted and completed the entire proposal in a
very short period of time;
(2)
the biochemical engineer and his colleague felt strongly that the proposal
they were writing represented a significant contribution to the field and an
important extension of their previous research efforts, and;
(3)
the biochemical engineer and his colleague felt that the proposal-writing
effort was a particularly challenging one since they were attempting to
merge two, previously unrelated, areas of technology-based research.
The data collected over this three-week writing period are in-depth. Since both
researchers wrote and re-wrote multiple drafts of the proposal on a day-by-day basis, I
was able to collect every draft of the proposal as it evolved from beginning to end (there
were 14 versions in all). In addition, during the three-week period, I was able to collect all
correspondence between the two writers; these were most often in the form of handwritten
slips of paper or electronic mail. Also, I taped two key meetings between the two
collaborators. Both meetings represented important junctures in the writing of the proposal
in that they centered around
83
(1)
the methodological implications of the two biochemical engineers’ datacollection techniques (i.e., the techniques which would provide them with
various types of data and how those data might be organized to form a
cohesive story);
(2)
the construction of the objects of study that they would be characterizing
(i.e., 10 model proteins); and,
(3)
the management of the overall proposal-writing effort (i.e., who would
write what sections and perform which experiments).
Finally, I interviewed the biochemical engineer for an hour and asked him to characterize
the collaborative effort, in terms of the planning, drafting, revising, and evaluative
aspects of the project, as well as in terms of the problems or difficulties that occurred during
the writing of the proposal.
The collaborative proposal-writing effort was, naturally, significantly influenced
by the biochemical engineer’s on-going proposal- and journal-writing activities. For this
reason, I collected drafts of a proposal that he was writing (and had set aside) when he
began the intense collaborative effort. Along with the drafts of the proposal, I took two
one-hour talk-aloud protocols of the biochemical engineer as he revised what he felt was
an important part of the proposal’s overall argument. In addition, I conducted three
thirty-minute discourse-based interviews with the biochemical engineer which focused on
the proposal’s content and on the “pink slips” (i.e., the reviewers’ comments) received from
an NIH review panel. My interest in his response to the reviewer remarks was predicated
by my assumption that the review process informs subsequent proposal-writing efforts
(Cole, Rubin, & Cole, 1977, 1978; Mitroff & Chubin, 1979; Myers, 1985a, 1985b, 1990).
84
Finally, along with looking at the two proposal-writing projects, I also collected
two drafts of a journal article that the biochemical engineer was composing subsequent to
writing the first proposal. In three open-ended interviews, I obtained the biochemical
engineer’s characterization of the two drafts, his research agenda, and his place in the
general field of biochemical engineering. While the majority of my results will emphasize
the three-week long, collaborative proposal-writing effort, I will draw on data collected
during these earlier journal-writing and proposal-writing efforts.
It should be noted that I believe my methodological approach differs significantly
from “traditional” approaches in the field of writing research in three important ways:
(1)
I did not privilege any one data-collection technique. I believe I obtained
reliable information about the proposal-writing process from a number of
sources (i.e., the protocol data provided me with valuable information
about the biochemical engineer’s revision process, the retrospective
accounts provided me with important information about the biochemical
engineer’s sense of the field and of what it means to contribute to existing
research in the field, the numerous drafts I collected provided me with
detailed information about how scientific texts evolve over time, and so
on).
(2)
Because I was interested in collecting very detailed information about the
proposal-writing process of a single biochemical engineer, I recognize the
contingent nature of my data; that is, I am careful not to make sweeping
generalizations about proposal writing in science and engineering. My
feeling is that the field of writing research, particularly research on
85
writing as it occurs in naturalistic settings, is still in its early stages and
that we can benefit from collecting numerous long-term case studies such as
this and adding them to a growing database of such studies.20
(3)
Since my data collection efforts have been influenced significantly by a
methodological approach called Participatory Design (PD) (explained in
detail in the next section of this chapter), I worked very closely with the
biochemical engineer, incorporating his comments and feedback
extensively, and relying on his skills and knowledge of the field to guide
my analyses.21
In the next five sections of this chapter, I describe the origins of the PD approach
and my incorporation of its working assumptions into my data analysis techniques. I then
describe my methodological approach for coding and analyzing the data collected about
20
21
In his excellent book, “Writing Biology: Texts in the Social Construction of
Scientific Knowledge” (1990), Greg Myers notes that an administrator who had
read an early draft of the book commented, “What do you expect me to make of a
study with an n of 2?” Myers response was, simply, “. . . with such case studies,
what number would be large enough?” (38). My response to the same charge (and
my n is 1 less than Myers’) is a similar one. My major goal in collecting
information about the writing processes and products of a single biochemical
engineer was to build a “detailed” picture of his composing activities over an
extended period of time.
The PD philosophy has important implications for the way one approaches the
task of collecting and analyzing data. Most importantly, emphasis is placed on
the conditional, evolving, and interpretive nature of the data analysis task.
Because my “study” of the biochemical engineer’s writing process incorporates his
interpretations of the process, I am less likely to describe behaviors that he,
himself, would deny, re-characterize, or flatly disagree with. Incorporating the
biochemical engineer into the research process has been a very positive experience;
as Myers (1990) points out, “In contrast to groups of nonscientists to whom I’ve
spoken, scientists have neither been surprised nor felt threatened by my comments
on scientific rhetoric. On the rare occasions when the subjects of these studies
have asked for a change or omission, it was always because I had left room for the
implication that they or someone else was guilty of fabrication, incompetence, or
bad management, or where they could be seen as criticizing or mocking other
scientists. Such implications could be seen as unscientific behavior, but my
discussion of their rhetoric never seems to have been taken as an attack on them as
scientists” (248-249).
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the three interdependent writing efforts under consideration. The first, and most intense,
writing project is the collaborative production of a research proposal written for NIH. The
second project is the biochemical engineer’s previous effort to produce and submit a research
proposal for NIH, as well as his interpretation of the review panel’s comments on the
proposal. The third project focusses on the biochemical engineer’s revisions to a journal
article submitted for publication to an eminent biotechnology journal. These three projects
are described using data from numerous open-ended and discourse-based interviews,
protocols, taped meetings, drafts of on-going writing, handwritten notes, computer
summaries of meetings, and the feedback of the biochemical engineer being studied.
A Participatory Design Approach to Data Collection
One might wonder what a methodological approach, derived from researchers
interested in software engineering and organizational management, has to do with a longterm case study of proposal writing in biochemical engineering. There are two answers to
this question. The first centers on methodological implications. That is, the PD approach
has evolved as a cooperative effort between two groups that have radically different
goals for working together and that bring to the collaboration significantly different types
of expertise and interests (software developers and users’ organizations). In addition, PD
also aims at finding strategies that can allow continuous interaction between the two
groups (Bjerknes, Ehn, & Kyng, 1987). In the present study, my interaction with the
biochemical engineer has been similarly difficult because the nature of his expertise
differs dramatically from the nature of mine.
The second implication that the PD approach has for a writing researcher
interested in proposal writing is a disciplinary one. That is, an important part of the effort
87
to understand writing as it occurs in the sciences and engineering is the need to familiarize
oneself sufficiently enough to take an “insider’s stance” towards the activities and
discourses that operate in the field under study.22 Just as Floyd (1987) and Thoresen
(1990), two prominent PD researchers, call for a transformation of the basic processes by
which software is developed, I too would argue for a similar transformation of the
processes by which we collect and study data about scientific and technical writing.
Thoresen (1990) criticizes current models of project organization as operating on positivist
assumptions:
Established models for project organization, project work, work analysis,
etc., are commonly based on implicit assumptions that the necessary
knowledge somehow exists, making the process of designing systems
mainly a matter of extracting the knowledge from the participants, be it
users or developers. More often than not, the assumptions do not hold.
Therefore, development projects need to be transformed from production
processes to mutual learning processes. Learning must be built into the
process, by changing the ways in which project work groups work
together [italics added] (34).
This perspective clearly emphasizes the iterative and complex nature of design and our
understanding of designs—and, in my case, of collecting data about scientific and technical
writing and of interpreting those data.
A PD approach to the study of scientific proposal writing, therefore, requires that
data be collected and evaluated by both individuals involved in the process—myself and,
in this case, the biochemical engineer. This orientation is not at odds with contemporary
concerns shared by sociologists of science, anthropologists, and ethnomethodologists.23
22
23
See Lynch (1982) for a pertinent discussion of the implications of taking an
insider’s stance versus taking an ironic stance towards the study of scientists and
scientific behavior. Also, see Collins and Harrison (1975) for a related stance.
They advocate that sociologists of science need to better educate themselves by
actually participating in the experimental and technical process of collecting data.
This debate owes much of its historical grounding in the debate between Geertz
(1973, 1983) and Clifford (1980, 1982, 1986). See Pearce and Chen’s (1989)
88
Steve Woolgar, in his (1980) article, “Discovery: Logic and Sequence in a Scientific Text,”
for example, begins his textual analysis by stressing the highly interpretive nature of his
discourse analysis. Like Woolgar, ethnomethodologist Michael Lynch (1982) criticizes the
traditional stance taken by sociologists interested in studying scientific activities and
discourse. In his (1982) book, Lynch questions the role of sociologists as impartial
“strangers” who go about observing scientists and categorizing them according to wellestablished sociological categories. As with researchers who employ the PD approach,
Lynch and Woolgar view data collection as an evolving and iterative process shared by
both the observer and his or her subjects of study.
Data Coding and Analysis
Given this perspective towards the biochemical engineer and his writing process,
the next four sections describe the data collected on the collaborative proposal-writing
situation, the proposal written prior to the collaborative situation, and the journal article
written by the biochemical engineer before he began writing the two research proposals
(see Table 1 for a brief summary of the data sources and their relation to each of the three
writing projects).
Collaborative NIH
Proposal
Raymond’s Earlier
Proposal
Raymond’s Journal
Article
excellent comparison of Geertz and Clifford’s positions regarding the interaction
between ethnographers and the groups they study. Unlike Geertz, who
championed “thick description,” that is, “fabricating fictions in order to render
coherent accounts of exotic cultures” (Pearce & Chen, 1989, 121), Clifford argued
“that ethnographic texts involve the on-going ‘give-and-take’ (negotiation of
reality) between the ethnographer and natives instead of the ethnographer’s own
reading and coherent (re)construction of the cultural texts” (Pearce & Chen, 1989,
128). For this reason, Geertz described his subjects as “informants,” whereas
Clifford preferred the term “Indigenous collaborators.”
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Open-ended
interviews
1
Discourse-based
interviews
Notes
3
3
12
Protocols
2
Drafts
14
Taped meetings
2
2
2
Table 1: Overview of the various data sources and their relation to each of the three
writing projects.
The method of analysis for these sources of data involved first extracting seventyone “episodes” (i.e., segments, individual topics, interview answers, or conversational
excerpts) from the four open-ended interviews, the three discourse-based interviews, the
two talk-aloud protocols, and the two taped meetings. In extracting the episodes for
analysis, I followed Potter and Mulkay’s (1982, 1985) advice regarding the extraction of
passages that focus on specific issues and topics. Extracting passages for detailed critical
analysis is a common practice in social psychology research since, as Mostyn (1985) points
out, “it is not possible for the final report to play back all of the recorded observations”
and, thus, “the researcher must think in terms of condensing, excising, and even
reinterpreting the data, so that it can be written up as a meaningful communication”
(138). 24
24
For guidance in extracting and analyzing the 71 episodes from the data that I
collected, I relied heavily on Brenner, Brown, and Canter’s (1985) collection of
essays on qualitative research methods, “The Research Interview: Uses and
Approaches.” In that edition, Canter, Brown, and Groat describe how to carry out
“restrictive explorations” (81) and Mostyn discusses “culling” one’s data-set to
facilitate interpretive analysis (138-139). I realize that, when extracting episodes
from a large number of data-types, the major problem to avoid is what George
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These episodes accounted for 42 percent of the total taped data (based on a word
count), and were first coded for whether they involved planning, revising, or evaluation.
In addition, the episodes centered around two of the three major research issues that I was
interested in exploring (and which were outlined in full at the beginning of this chapter):
(1) audience considerations, that is, how the proposal writer(s) characterized their
perceived audience or how they characterized potential problems or responses that the
intended audience might have with the proposal; and, (2) the relationship between
proposal writing, the scientists’ use of various rhetorical strategies, their understanding of
the discourse conventions of the field, and the on-going scientific research being carried out.
Appendix D gives a detailed breakdown of the numbers and percentages of each episode in
relation to each type of data collected.
Eight out of the 71 episodes, or approximately 11 percent of the episodes
(distributed evenly over the different data types), were coded by two raters, and then
another 27 episodes were rated independently by the same two raters to insure reliability.
Interrater reliability on the 27 episodes (almost 40 percent of the total episodes coded)
reached 86 percent. Forty-seven percent of the episodes were collected during the
collaborative proposal-writing project; 22 percent of the episodes from Raymond’s earlier
proposal-writing effort, and 31 percent of the episodes from his article-writing project.
The majority of the remaining 58 percent of my data emphasized technological
details regarding enzyme purchases, equipment availability, budget allocation plans,
administrative details, and project management.25 For example, although the episodes
25
(1959) has called “circularity,” that is, defining a series of hypotheses or goals for
one’s research and then choosing data that allow one to see what one wants to see
(cf., Mostyn, 120-124).
Although the pragmatics of scientific experimentation and laboratory practices
were not the focus of this dissertation, numerous sociologists of science and
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taken from the open-ended interviews only account for about half of the total data
available, the majority of the unexamined data emphasized the biochemical engineer’s
perceptions of the history of his field and his research background, two subjects that were
not the focus of my study.
In addition, because of my interest in how proposal-writing projects are managed, I
noted any references to project assignments (during the collaborative meetings in
particular) and any references to the general time-line involved in producing a written
proposal (most often made during the open-ended and discourse-based interviews). Since I
had all 14 drafts of the collaborative proposal, I also traced any changes made to the
proposal and contrasted them with the plans made during the two meetings and with the
notes exchanged between the two biochemical engineers.
Analysis of the Collaborative NIH Proposal
As described earlier, the proposal-writing effort that my study emphasizes took
place over a three-week period, from September 10th to October 1st, 1990. Although the
writing of the proposal began on September 10th (when Raymond created a file which
included a brief introduction of the research problem and specific aims, a description of
Larry’s IMAC experiments (Immobilized Metal Affinity Chromatography), and a
description of some of Raymond’s earlier experiments using Differential Scanning
Calorimetry—DSC—techniques), actual discussions between Larry and Raymond about the
idea of writing a collaborative proposal first took place in March of that year. Then, in
the first week of September, Raymond received an announcement from the NIH describing
technology have done interesting research in this area, for example, Collins and
Harrison (1975), Knorr-Cetina (1981), Latour and Woolgar (1979), and Woolgar
(1981).
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an upcoming study section on metalloproteins. The Request For Proposals (RFP) stated that
October 1st was the due date for submission, a date which Raymond and Larry were
optimistic about being able to meet.
The data collected during the production of the 22 page proposal consist of 14 drafts
of the proposal which I analyzed in the following ways:
(1)
for syntactical evolution, that is, for changes in the average length of
words, sentences, and paragraphs, and for prepositional phrases and
passive voice constructions;26
(2)
for organizational evolution, that is, for changes to the text in the form of
additions, deletions, and movements,27 and
(3)
for planned evolution, that is, for changes that were the result of specific
interactions either during the two taped collaborative meetings or through
documented notes imbedded in the on-going texts.
The two, taped collaborative meetings lasted approximately two hours each and
clarified why certain collaborative experiments and elements of the proposal were
altered, created, or eliminated. These data, along with the numerous notes and general
comments that the co-authors included in their various drafts, emphasized the “informal”
nature of the collaboration. Along with coding the meetings and open-ended interviews for
audience considerations and so on (described in the above section), I also coded them for
proposal-management details, that is, for any reference by either of the biochemical
26
27
I used a Macintosh-based program called Grammatik•Mac™ to trace these
alterations across the fourteen drafts.
I used a Macintosh-based program called OmniProof™ to trace additions, deletions,
and alterations to the fourteen drafts.
93
engineers to planned writing assignments. This allowed me to trace any plans for writing to
the actual drafts produced before and after the two meetings (as well as across the other
drafts).
Analysis of Raymond’s Initial Proposal Effort
To supplement the collaborative proposal-writing data, I interviewed Raymond
about two drafts of a proposal that he was writing prior to beginning the collaborative
proposal effort. The first draft had been created before he received a review from the NIH
panel members, and the second was written following the review. I coded both the
protocols of the writer (taken while he revised a section of the proposal based on the peer
review) and the discourse-based interviews which emphasized different aspects of his
new draft as well as the reviewers’ comments and feedback. As explained earlier,
approximately 40 percent of the episodes I collected from the protocols and the interviews
related to the first proposal were coded with an independent rater to estimate reliability.
Analysis of the Journal Article
The biochemical engineer’s published study of yeast alcohol dehydrogenase
(which he published with four other researchers) is the product of years of research and
writing. For the purposes of my study, I concentrated on two particular drafts—the first
draft that the biochemical engineer sent to the journal for submission and the first re-write,
based, for the most part, on the reviewers’ comments. During three open-ended interviews,
I familiarized myself with the biochemical engineer, his research team, facilities and
equipment, his perceptions of the research field, and his description of the evaluation and
revision processes. The interviews lasted between thirty minutes to one hour each (see
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Appendix E for a list of some of the questions asked of the biochemical engineer).
Although the questions were general and his answers retrospective, they allowed me to
understand more thoroughly and to evaluate the biochemical engineer’s motivation and
texts (which acted as the focal-point of the interviews). In particular, these meetings
provided me with 20 episodes that contained valuable information about his perceptions of
the biochemical community and his place in it.
Collected Iterations on Data Interpretations
Finally, and in keeping with the PD orientation of my data-collection efforts, I
kept on-going notes of interactions I had with Raymond throughout the process. In
particular, I noted any differences we had in characterizing his writing process. As well, I
gave Raymond two drafts of my results section, and obtained (and integrated) any
comments or feedback he offered. As I pointed out earlier, my incorporation of his feedback
had important methodological and disciplinary implications; my goal was to work w i t h
the biochemical engineer to better understand his writing processes, rather than to attempt
to characterize his writing in isolation. Thus, I encouraged Raymond to freely question,
comment on, or criticize any interpretations I made (verbally or in my written texts) about
his writing processes and products.
In the next chapter, I will discuss the results of the two-year case study. In
particular, the results emphasize how two proposal writers in biochemical engineering
constructed the intended audience for their proposal, how proposal writing influenced
their scientific research, and how frequently they made rhetorical decisions based on their
sense of the potential audience for the proposal and the well-learned discourse conventions
of their field. In addition, I will describe the management of the collaborative proposal-
95
writing project, as well as identifying some of the problems or difficulties that the two
collaborators encountered during that project.
96
Chapter 5—Results of the Case Study
. . . in there I kind of shot myself in the foot. I said, well, it could be an
impurity, but I don’t think it’s an impurity, and I just moved on. And . . .
the guy that really wanted to torpedo this, highlighted that line. So
that was an example, you know there’s good things in there, and the
experience, a lot of things we did were defensive in nature. Kind of,
yeah, we’re seeing effects, controlled experiment, we’re seeing effects,
controlled experiment. But there was one thing that we didn’t even have
to say. It’s an example, if you editorialize too much, the thing gets too
long, it puts a gap between what you see and what you’re saying, and it’s,
the best thing is to write down everything in your mind, then go back and
rip it out.
Third open-ended interview with Raymond, the biochemical engineer.
What can we know? That is, what can we be sure we know, or sure that
we know we knew it, if indeed it is at all knowable. Or have we simply
forgotten it and are too embarrassed to say anything? . . . By “knowable,”
incidentally, I do not mean that which can be known by perception of the
senses, or that which can be grasped by the mind, but more that which
can be said to be Known or to possess a Knownness or Knowability, or at
least something you can mention to a friend (28-29).
Allen, W. (1966, 1989). Getting Even. Without Feathers, Getting Even,
Side Effects. NY, NY: Quality Paperback.
Raymond’s Background and Research Interests
My major source of data are from an Associate Professor in biochemical engineering.
Raymond did his Ph.D. in biochemical engineering at Cornell University. He is the
recipient of a 1987 Presidential Young Investigator Award, and has been working at
Carnegie Mellon since 1983, where his main research focus has been on the following three
areas:
97
(1)
cellular processes, that is, characterizing and developing a protein
expression system for use in high density cell culture; modeling cellular
processes and mapping the properties of metabolic networks;
(2)
proteins/enzymes, that is, investigating the molecular-level processes
involved in the deactivation of membrane surface-bound species; and
modulating the transport rate of proteins across membranes through the use
of ligands, and;
(3)
bioprocess design, that is, building mathematical frameworks for the
analysis of retrofit problems in bioprocess engineering and integrating cell
biology/biochemistry into process screening and design.
Not surprisingly, the graduate student theses that Raymond is supervising also
reflect his research interests; some of these theses are as follows: “Activity and
Deactivation of Multiple Species of Membrane-Bound Yeast Alcohol Dehydrogenase,”
“Structure-Property Identification in Metabolic Networks,” “Hindered Diffusion of SelfAssociating Proteins,” “a-Chymotrypsin Diffusion in Ligant Gradients,” “Enzyme
Transport in Ligand Gradients,” and so on. Journals that he has published in previously
include “The Journal of Theoretical Biology,” “Biotechnology Bioengineering,” “The
World Biotechnology Report 1984,” “Chemical Engineering Journal,” “Biosystems,” and
“Biotechnology Progress.” He has twenty-two publications in total, dating back to 1984.
With the exception of four articles, all the publications were collaborative efforts.
He has taught courses on advanced heat and mass transfer, unit operations of
chemical engineering, biological transport and pharmacokinetics, and transport
phenomena. In addition, while at Carnegie Mellon, he has developed three new courses:
98
computational biology on network analysis, fermentation technology (which he taught
jointly with a molecular biologist), and biotechnology for technology and people, which is
a first year course for all engineers. Importantly, his major contribution to the technology
and people course has been his emphasis on writing and communication in the sciences and
engineering.28
His continued involvement in the funding process, he points out, reveals—not only
his professional duty as an active academic researcher—but also his on-going desire to “get
a peek at the inside operations of the funding networks.” To this end, he has served as a
review panelist for the Office of Naval Research (June, 1985), for the NSF (September,
1988, and May, 1990), and for the National Research Council (August, 1990).
Indeed, Raymond’s funding activities begin prior to his completing his Ph.D.
These grants take three forms: (1) equipment grants from nonacademic organizations, for
example, Aluminum Company of America, Perkin Elmer Company, and DuPont; (2)
equipment grants from foundations, for example, Keck Foundation, Faculty Development
Grant, and Fisher Life Science Group, and; (3) research grants from government funding
agencies, for example, NIH and NSF. The grants range in dollar value from $5,000 to
$200,000. Not surprisingly, many of his early funding efforts were carried out in conjunction
with his thesis supervisor. Once at Carnegie Mellon, his proposal collaborations began
with senior faculty and have recently shifted to collaborations with other, junior faculty
(Assistant and Associate Professorial level) and his own graduate students (probably a
function of his movement towards seniority).
28
Based on many of our initial conversations, in fact, he designed exploratory studies
to see how his students wrote and read scientific journal articles. His findings
disappointed him: students wrote and read very linearly, a strategy, he observed,
that rarely guided experienced scientific practice.
99
Because my study emphasizes two proposals prepared for a government funding
agency, it is worthwhile listing the progression of government grants that he has received.
His funding began in his first year of his Ph.D. program, May, 1984, when he received a
Research Initiation Grant from NSF to study biochemical reaction networks. NSF funded
him from March, 1986, to August, 1987, to study membrane-bound alcohol dehydrogenase.
From August, 1986, to January, 1988, he and a colleague were funded by NSF to study the use
of ligand gradients for protein separation. He was co-principal investigator with the same
colleague for a large grant from NSF from February, 1988, to July, 1991, to study a similar
technique. And finally, in August, 1989, he received an NIH grant for approximately
$30,000 to investigate NMR and a fluorescence spectroscopy-cultivation system.
Raymond’s Context for Writing
Although I began collecting data on Raymond’s research activities, journal writing,
and proposal-writing goals during May, 1988, the initial proposal-writing effort that my
study describes dates back to December, 1989. This initial proposal, and one of the two
proposals that my dissertation emphasizes, is still in preparation and is expected to be
submitted to the NIH. There are several reasons for Raymond’s delaying to submit the
proposal to the NIH.
First, the proposal, originally entitled “Calorimetric Comparison of
Dehydrogenase Structures,” owes much of its development to an article that Raymond
began writing in May, 1988 (see Appendix F for a chronological summary of the three
writing projects spanning over the two year period). That article, the culmination of
approximately four years of laboratory research and writing, was entitled
“Microcalorimetry and Fluorescence Study of Yeast Alcohol Dehydrogenase: Stability and
100
Heterogeneity Implications,” a title which highlights its relationship with the initial
proposal’s subject-matter. Raymond acted as the article’s main author in collaboration
with four other authors. The journal article was submitted to “Biotechnology Progress”
approximately the same time he began writing the first research proposal.
As Myers (1990) has pointed out, the interaction between journal writing and
proposal writing in science and engineering is often an intense one, as was certainly the case
for Raymond and his colleagues. The article was peer reviewed, accepted pending
revision, and returned to him in July, 1988. However, feeling that the article contained
several problematic gaps, Raymond and his graduate research team turned their attention
back to the laboratory. This re-orientation, in turn, halted his work on the original
research proposal. After four months, numerous experiments, and various drafts of the
journal article, Raymond re-submitted a much revised paper entitled, “Microcalorimetry,
Fluorescence, Fractionation Study of Yeast Alcohol Dehydrogenase: Stability and
Heterogeneity Implications.” The article was sent to the same journal in May, 1989, and
ultimately accepted by “Biotechnology Progress.”
The ultimate title of the journal article reflects an extension in Raymond’s research
approach that he would eventually incorporate into his research proposal; his latest
version of the research proposal and its title—“Comparison of Dehydrogenase Structures
by Microcalorimetry and High Pressure Studies”—in turn, represents one major extension
from the journal article research he was carrying out. The first extension to his research
goals, reflected in the journal article’s title, is an extension of his instrumentation and
data-collection tools, that is, the use of both microcalorimetry and of multiple highpressure techniques. His revised proposal, as well, extends the work described in his
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journal article, and aims to compare numerous classes of dehydrogenase, rather than
studying yeast alcohol dehydrogenase specifically.
While working on the proposal, Raymond was solicited to collaborate with
another group, and that collaboration has now lead to a much-expanded, joint NIH
proposal. The collaborative proposal, as I will refer to it throughout the dissertation, was
completed and submitted to NIH in October, 1990, and is the centerpiece of my case study.
Writing began on September 10th, 1990, and it was submitted for review to NIH on October
1st, 1990. The September 10th version of the proposal (ultimately, I collected all 14 drafts
that the biochemical engineers produced) consisted of a draft of the specific aims of the
research (there were eight aims), the significance of the research (which included a
cursory background and literature survey as well as a draft of the proposed contributions of
the research), the results of preliminary efforts and discussion sections (in terms of the
IMAC experiments and the DSC experiments), the proposed research (the choice of model
proteins and their construction), and two appendices (materials and methods).
The remainder of this chapter is organized as follows. The next section describes
the overall results of the analysis of the 71 episodes (accounting for all three writing
projects). As described in Chapter 4, out of the 71 episodes, 47 percent centered around the
collaborative proposal-writing project, 22 percent centered around Raymond’s earlier
proposal-writing effort, and 31 percent centered around his journal-writing project.
Therefore, after presenting the combined findings of all three writing projects, the next
three sections describe each individual project in detail. Finally, I present the analysis of
the 14 proposal drafts collected from the collaborative proposal-writing project; the
analysis emphasizes, in particular, the interaction between the two biochemical engineers’
plans and goals for the written proposal and the actual text produced over time.
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Raymond’s “Web of Writing”
In analyzing all three writing projects, together and individually, I characterized
each of the 71 episodes according to the following global categories (also, see Chapter 4):
•
the type of data-collection technique used (e.g., taped meeting, open-ended
interview, talk-aloud protocol, etc.), and;
•
whether the episodes emphasized the planning, writing/revising, or
evaluating of the document.
Within each of the above categories, I also coded for examples of the following (see
Chapter 4 for reliability ratings):
•
Characterizing the audience according to its sub-specialty, background,
values, and so on.
•
Anticipating audience reactions to the proposal or to the proposed
research.
•
Altering existing research plans to accommodate the writing of the
proposal.
•
Integrating existing scientific research (literature) into the proposal or
research plan.
•
Identifying technical issues and constraints affecting the data-collection
process.
103
•
Discussing rhetorical alternatives or strategies affecting the writing of the
proposal.
The percentage of episodes taken from each of the four data-collection methods
were as follows: 49 percent from the open-ended interviews, seven percent from the
discourse-based interviews, 16 percent from the talk-aloud protocols, and 28 percent from
the taped meetings. My interest in the methodological implications of different types of
data was predicated by Gilbert and Mulkay’s (1984) hypothesis that different methods
solicit different types of responses from scientists (see Table 1 of Appendix G for a
percentage breakdown of the different data-collection techniques in relation to planning,
writing/revising, and evaluating).
I collapsed the writing and revising categories for two reasons. First, the majority
of the data were collected during various types of interview situations (discourse-based
and open-ended), and during the two meetings held by the biochemical engineers. These
forums, of course, involved no actual composing. Second, during the two talk-aloud protocol
sessions (where one would expect original composing to occur), Raymond revised existing
texts and tended to describe his revision process rather than to talk as he transcribed new
text. 29
It is important to note, however, that although my data-collection methods did
not elicit more information about the transcription processes of the biochemical engineer or
his colleague, they did provide me with an interesting source of information about how
they planned, revised, and evaluated their scientific texts. The open-ended interviews
29
See Cooper and Odell, 1976, and Cooper and Holzman, 1983, for discussions of
the difficulties that experienced writers frequently encounter in talk-aloud
situations.
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made up 16 percent of the episodes involving planning (or discussions about planning) and
the taped meetings provided another 28 percent (for a total of 44 percent). Thirty-two
percent of the open-ended interviews and six percent of the discourse-based interviews (a
total of 38 percent) centered on text evaluation (or talk about text evaluation). And, as one
would expect, the talk-aloud protocols provided the most significant source of data for the
writing/revision process (a total of 18 percent). In interpreting these numbers, by the way,
it should be remembered that the overall breakdown into the three writing processes
(planning, writing/revising, and evaluating) is also a function of the percentage of episodes
that made up each of the four data-collection types (see Appendix D for those statistics).
Also, because the open-ended interviews, discourse-based interviews, and taped meetings
involved talk about texts, it is likely that planning and evaluation are more appropriate
venues for these sessions. Thus, the proportion of activities is related directly to the mean
number of words per episode.
In addition to coding for the interaction between the different data-collection
techniques employed and the type of writing process represented by those techniques, I also
coded all three writing projects for how frequently the biochemical engineers’
characterized their audience, anticipated audience reactions, altered existing research
plans, integrated existing scientific research into their texts, identified technical issues,
and discussed rhetorical alternatives. My discussion of Raymond’s writing processes,
therefore, combines detailed descriptions of rhetorical moves that Raymond made when
planning, writing, and evaluating his texts with quantitative summaries of the frequency
with which such activities occurred.30
30
Berelson (1971) has discussed the tension in qualitative research “between
frequencies and real meaning,” a dichotomy which Mostyn (1985) describes as
“fallacious . . . since the determination of all categories [for quantitative analysis]
involves qualitative judgments in the first instance” (121). Therefore, although
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Table 2 of Appendix G is a percentage breakdown of the six categories for all 71
episodes. These categories (e.g., characterizing the audience, integrating existing
scientific research, and so on) were also coded for when they occurred during the writing
process, that is, whether they occurred during planning, writing/revising, or the
evaluation of the text being produced.31
Notably, only four of the activities in Table 2 occurred in isolation, that is,
without another activity being simultaneously referred to or carried out. Instances where
the biochemical engineers emphasized one category accounted for the following overall
percentage of the 71 episodes: they characterized their audience in four percent of the
episodes, anticipated audience reactions to their text in four percent of the episodes,
altered existing research plans in seven percent of the episodes, and discussed rhetorical
strategies in 15.5 percent of the episodes. Importantly, discussions of and references to
alternative rhetorical plans and strategies dominated the 71 episodes (71.5 percent) and
played a significant part of all the coded activities (56 percent were co-coded with the
five other categories).
The highest interaction between activities existed between accounting for the
perceived audience of the text and generating rhetorical strategies for producing the text.
That is, audience concerns accounted for 52 percent of the 71 episodes, and the biochemical
engineers appeared to emphasize rhetorical alternatives when accounting for the
audience; to that end, 35 percent of the points made about possible rhetorical strategies
31
obtaining interrater reliability insures that the defined categories are somewhat
generalizable, it is important to acknowledge the contingent nature of frequency
data
See Flower, Schriver, Carey, Haas, and Hayes, 1989, for a review of the research
on composing and the planning process; Hayes, Flower, Schriver, Stratman, and
Carey, 1987, for a review of revision and evaluation, and; Hayes, 1989, and Hayes
and Flower, 1980, for a description of the writing process in general.
106
were made in conjunction with points made about the perceived audience of a text. The
following excerpt, from the first taped meeting between the two biochemical engineers,
exemplifies how discussions of audience concerns interacted with discussions of rhetorical
strategies:
Raymond: 1 Yeah. That I think is a good closure, and I think a good
defensive move too. 2 Because, you know, anybody that spends time
reading the proposal, they might react invertibly first, and then they go
home and they sleep on it and come back the next morning, and they get
like, you know, gee-wiz, they didn’t talk about this or that.
Larry: 3 Yeah, I think that’s something we need to talk about at least
and show it, where we’ve considered that, where this metal is.
Raymond: 4 Okay then maybe that could drive the, so maybe we’re
talking about the aims list, adding that as sort of an additional aim
(Taped meeting).
In sentence 1, Raymond is referring to an argument he and Larry are making in the
written proposal. His reaction to the text is clearly evaluative, and leads naturally into
considerations of audience reaction (sentence 2). Implicit in Raymond’s characterization of
the proposal’s audience is his assumption that they will read and re-read the document
several times looking for potential oversights or shortcomings. In sentence 3, Larry agrees
with Raymond’s assertion and, in sentence 4, Raymond brings the conversation back to the
written proposal, suggesting that they add the argument as an additional aim to the
Specific Aims section of the proposal. In this way, audience orientation prompts the
biochemical engineers’ goal of finding appropriate rhetorical strategies.
Table 3 of Appendix G shows the activities that the biochemical engineers’
engaged in during the planning stage of the writing process. Again, references to
alternative rhetorical strategies dominated the planning episodes (72 percent). Similarly,
the biochemical engineers spent a considerable amount of energy describing and
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anticipating potential audience reactions to their documents (59 percent). As with the
interaction between audience concerns and rhetorical strategies, audience characterizations
often interacted with audience anticipation:
Interviewer: How did considerations of audience inform the writing of
your proposal?
Raymond: 1 Yeah it had a bearing on several things because when you
looked at the list, we noticed that they were largely chemists, and
maybe biophysical chemists, and their bent would be very microscopic
and molecular. 2 And we spotted the engineers, and the affiliations we
saw, we didn’t detect whether anybody on that group would be
collaborating with people we knew. 3 But the message we got was
there’s going to be chemists there, so we should be pretty careful, in our
decisions, we’re talking about things that they would probably know a
lot more about than we would. 4 So either we’d avoid talking about it, or
just kind of expose our ignorance, or do it sloppily, or make sure it gets, it
looks at the right things, and then they would get the idea that we kind
of knew what was going on. . . . Based on that it was sort of trying to
imagine what other kind of proposals would show up and get reacted to,
and where ours was supposed to fit in. 5 Since I saw mostly chemists in
this place, I thought, well, the majority of proposals that were going to
be attractive were probably going to be, probably emphasizing other
techniques and very microscopic stuff using nuclearmagnetic resonance or
high-powered techniques, a way of looking at molecules, you know,
something like that. 6 We were coming at it from a fundamental
viewpoint, but from a more practical overall perspective. 7 And that, I
think we identified a number of issues that were going to be critical to
the ultimate use of the technology that we were talking about here. 8
And, so the bottom line is . . . my thought was we should really
emphasize two key points throughout the proposal that would probably
set it apart from other proposals that they would be looking at (Openended interview).
In the excerpt above, Raymond discusses how the perceived audience for the
proposal influenced the proposal-writing process. Earlier, he had pointed out that the list
of panel members provided by NIH had formed the basis of several discussions between
him and his collaborator. The list, which consisted of the names and institutions of
potential reviewers, did not contain information about their particular specialties,
information that Raymond is quick to supply in sentence 1. Not only does he refer to their
108
research areas, but this reference also informs his understanding of the type of research
they would typically carry out (“very microscopic and molecular”). In sentence 2,
moreover, Raymond reveals that one of his goals for looking at the list of reviewers is a
political one; that is, he points out that none of the reviewers appear to be working with
groups that “would be collaborating with people we knew.” His realization that most of
the reviewers would be chemists also influences the content of the proposal (sentences 3 and
4) and the proposal’s place in the group of other potential proposals submitted to the
reviewers (sentence 5). Finally, Raymond’s characterization of the audience ultimately
informs his sense of how his proposal differs from the other proposals (sentences 6, 7, and
8).
The two key points that Raymond felt would make his proposal stand apart from
the others received by the review panelists were as follows. First, the proposal was about
a separation technique, where the goal was to take an extract containing millions of
proteins from a cell. Their separation technique allowed them to extract a desired protein
out of that cell mixture, which was accomplished by establishing which proteins had
affinities for which metal ions, where the metal ion was mobilized in some kind of
stationary phase. Most proteins that have an affinity for metal ion “absorb back in” or
“pass through” the desired material, so the biochemical engineers could simply target and
“grab” the one that they were interested in analyzing. In addition, they could “tune” the
one that they were interested in through engineering or genetics. Raymond’s belief was
that the reviewers, which were largely chemists, would want to look very specifically at
one protein and one metal ion, and to detail the interaction between the two. He and Larry,
however, in addition to being interested in the principle interaction, were also interested
in background affects; that is, if there were any holes in the background:
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Raymond: 1 If there’s any holes in the background where you have a
contaminated one, it won’t pass through or stick, and you might want to
aim the one you’re interested in kind of through that window, kind of
fishing. 2 So kind of emphasize this window thing, and you’ve got to
know that background; without that background you can’t engineer
rationally. And that was one thrust (Open-ended interview).
According to Raymond, the second “thrust” would be much more familiar to the
audience of chemists, that is, characterizing the interaction between the protein and the
metal ion. As Raymond summarizes:
1 Those two things, that’s pretty much what the proposal was hung on. 2
There’s a window, use the window, fine-tuning, and then the interaction
thing, and try and study that and get a logical set of model proteins. 3
Work on more than one protein; work on some that have subtle
differences, and focus on that, and hopefully that model set covers
enough situations that you can get some generalities out of it too. 4 That
was kind of thinking ahead, but when we saw the audience we kind of
started changing the emphasis around a little to try and work this with
that audience (Open-ended interview).
Table 4 of Appendix G represents the activities the biochemical engineers
performed during the writing/revising stage of the composing process. As with the
planning stage, the writing/revising process involved numerous references to rhetorical
strategies (91 percent) and to audience anticipation (17.5 percent). In addition, as one
would expect during this stage, Raymond paid careful attention to how and where to
incorporate appropriate research literature into his text (23.5 percent):
Raymond: 1 I just re-read the section, and it strikes me that the way it
was originally set up was to show how with pressure techniques we can
parallel what we propose to do with calorimetry and thereby come to
conclusions with two independent methods. 2 But reading it, I think the
best way to change this is to attack the first paragraph, put a couple of
new sentences in, and then use the examples I already put in here as, just
basically the means to underscore some of the introductory sentences I put
in. 3 And then, somewhere in there, try and make a second paragraph,
and show how some of the ideas that we’ve discussed, the conclusions
we’ve got from calorimetry, how they didn’t always agree with this
fellow Smith’s studies of these enzymes using the single-pressure
technique he developed (Talk-aloud protocol).
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The above excerpt is representative of the many instances in which Raymond
alternated between his knowledge of the field’s scientific research literature and his goals
for the proposal’s line of argumentation. After re-reading a section of the document
(sentence 1), Raymond decided to add some examples to clarify his argument (sentence 2).
As well, he decided to add another paragraph that juxtaposed his calorimetry results
with Smith’s results. Another example of references to the research literature is as
follows:
Raymond: 1 I’ve got a copy of the proposal on one side, and some articles
here, and what I’m going to do is try and re-work section 5.4 a little bit,
in light of some articles a referee on a paper provided us with plus in
light of a review article [one of my graduate students] found in the
library (Talk-aloud protocol).
This excerpt reveals that writing and reading scientific literature are, for Raymond, very
interdependent activities. Moreover, his understanding of the research of other scientists
is highly strategic; that is, he often defines his own research agenda by setting it apart
from his interpretations of others’ research.32 The following excerpt incorporates
Raymond’s sense of what other researchers are currently doing combined with his “angle”
on where his research fits into that research:
Raymond: 1 There’s been a lot of theory and not too exciting but
repetitive development of kinetic pencil-and-paper models from a group
down, some school south of here. 2 And some guy’s cranking out
theoretical models and he’s making the assumption it’s there. 3 And
then there’s some experimental work going on where people showed that
for some surface-attached molecule preparations that it might be there
too, although some question marks whether they were interpreting their
data.
Interviewer: Question marks from you?
32
For an interesting study of innovative behavior in science and engineering, see
Kasperson’s (1976) dissertation. In his study of sixty scientists, Kasperson found
that innovative scientists tended to pay careful attention to the work of their
colleagues and peers.
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Yes. 4 Well other people too. 5 It’s very possible but there’s probably
other ways to interpret their data too. 6 But they’re kind of, this is the
question they’re after so, you know, the results filtered the way they’re
thinking about it. 7 So you’ve got guys doing theory, some experimental
work. 8 We thought that if we could show, at a more fundamental level,
the unfolding of a molecule as a complex process or calorimetry could
show that the denaturation of the whole thing is not a simple one-step
process, then there’s some neat evidence here that support the guys doing
theory and add to what these other guys might have done in terms of
experimentally showing it’s there (Open-ended interview).
Not only does Raymond show a familiarity with the work of other researchers (sentences
1, 2, and 3), but he also points out what he feels are some of the shortcomings of their
research (sentence 3). In sentence 4, he emphasizes that others agree with his assertion
and, in sentences 5 and 6, he explains why he has problems with current research in the
area. In Raymond’s words, the researchers’ experimental question “filtered the way
they’re thinking about it” (sentence 6). Finally, Raymond centers his research technique in
the theory and models of existing research, hence establishing his potential contribution to
the field.
Table 5 of Appendix G shows the activities that the biochemical engineers
engaged in during the evaluation stage of the composing process. Interestingly, almost 20
percent of the evaluation episodes (as with the planning episodes) referred to the need to
re-define existing research plans while writing the proposal:
Raymond: 1 I mean, for the project you have to demonstrate that what
he’s doing in the lab works and it’s feasible and you have to demonstrate
that the techniques that we hope to do are feasible and will work. 2 So
before that’s done then there’s no possibility for a research plan,
actually the way it’s being conducted. 3 And what you’ve got is the
proposal and without that there’s no preliminary effort. 4 So I think
that they kind of map pretty well. 5 The relative proportions I think
change though. 6 Like, for this proposal, since the emphasis was on
chrometography techniques, we might have been able to make the
proposal a little more hypothetical. 7 But in the proposal it was
probably more critical for him [Larry] to have decent preliminary data
to report and make a decent case for the mutations the protein’s using to
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pull those off. 8 And we could have talked about some characterizations
stuff in more of a round kind of way, and referred less to the literature for
legitimacy of what we were going to attempt to do in conjunction with his
work. 9 So with a proposal you kind of need both things. 10 But it’s like
the weighting changes. 11 Before you can actually go ahead, then we
need experiments from my lab to really show that this is a worthwhile
thing, not just something to pitch in a proposal (Open-ended interview).
Raymond, in characterizing the interaction between the written proposal and the planned
research goals, points out that questions of feasibility drive both activities (sentence 1).
The two activities, therefore, “map pretty well” (sentence 4), with plans being made in the
proposal informing laboratory activities and visa versa. “Hypotheticality,” moreover,
hinges on how much preliminary data they report in their proposal (sentences 6 and 7).
That is, Raymond understands that the more data they are able to report, the less they
have to refer to “the literature for legitimacy” (sentence 8).33 This finding supports the
notion that written proposals are less proposals to “begin” a particular line of research,
and more proposals to extend, refine, or build on research that is currently being carried out
(cf., Bazerman, 1988). And it also undermines the stereotypical notion that proposal
writing occurs “before” the major activities of researching and writing up experimental
findings.
To summarize, Raymond exhibited a broad range of complex strategies in his
writing efforts. In particular, discussions of alternative rhetorical strategies dominated
33
My use of the term, hypotheticality, is consistent with the terms of numerous
other researchers interested in how scientists’ couch or qualify their results in the
context of existing research frameworks: Harvey (1981) uses the term,
“plausibility,” Latour and Woolgar (1979) refer to textual “modalities,” and Latour
(1988) discusses how scientists “shift in” and “shift out” in their texts. Gross
(1989) has referred to this tension between contributing scientists and the scientific
communities which surround them as “the paradox of communal competitiveness:
while the general progress of scientific knowledge depends heavily on the relative
subordination of individual efforts to communal goals, the career progress of
scientists depends solely on the recognition of their individual efforts” (89).
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the data and interacted with all five coded rhetorical moves (36 percent of the total
episodes contained an rhetorical move in isolation, while the remaining 64 percent
contained groupings of two rhetorical moves). Table 1 highlights the major interactions
between various rhetorical moves for all 71 episodes:
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Rhetorical Moves
# (% of total
episodes)
# (% of total
episodes)
Char. Aud. (1) to
Rhet. Alts. (6)
4 (40%)
10 (15%)
Ant. Aud. (2) to Rhet.
Alts. (6)
11 (61%)
18 (25%)
Alt. Res. (3) to Rhet.
Alts. (6)
2 (29%)
7 (10%)
Int. Sci. Res. (4) to
Rhet. Alts. (6)
6 (75%)
8 (11%)
Disc. Tech. (5) to
Rhet. Alts. (6)
2 (66%)
3 (4%)
Rhet. Alts. (6) to
Ant. Aud. (2)
8 (32%)
25 (35%)
Total
33 (47%)
71 (100%)
Table 1: Overview of the interaction between activities performed by Raymond during all
three writing projects. The table is read as follows: there were 10 episodes (15 percent of
the total 71) that contained a characterization of the audience (Char. Aud.), and the
majority of the characterizations of the audience led to a discussion of available
rhetorical alternatives (Rhet. Alts.)—or 4 episodes out of the 10 (i.e., 40 percent).
As the frequency data indicate, attempts to anticipate the audience most often led
to discussions of alternative rhetorical strategies (25 percent of the total episodes).
Similarly, discussions of rhetorical strategies frequently led to descriptions of audience
expectations and potential problems (35 percent of the total episodes). Importantly,
although it was not in the scope of this particular project, future research will need to
address the quality and effectiveness of these rhetorical strategies in the light of the
reviewers’ and editors’ reactions to the texts being altered.
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In the next three sections, I describe the results of the analyses of the three writing
projects. The collaborative proposal, created by Raymond and Larry, is the result of an
intense, three-week writing effort, and is described in detail in the next section.
The Collaborative Proposal-Writing Project
Raymond, in characterizing his collaborative proposal-writing project, makes the
following statement:
1 This [collaborative effort] was a bit unique because, in the past, the
collaborations were more that our particular effort was pretty far along
and we needed to get a few experiments done, employing a different
technique or something. 2 You’d call somebody up and see if they could
run a quick experiment, and, by doing that, throw that into what you’ve
done and have a more complete package (Open-ended interview).
What made his current experience both challenging and frustrating for him, was the fact
that he was not simply “slotting” the research of another colleague into his current
research agenda or into a well-established line of inquiry; nor was he merely employing
someone else’s laboratory technique or methodology in order to strengthen his research
argument. In this case, he stated
1 We were trying to blend two different universes together and make
something, you know, a stronger overall package. 2 So there was not
really any working back and forth between two labs. 3 It was a merging
of two independent things (Open-ended interview).
Table 6 of Appendix G gives a breakdown of the various activities performed by
the Raymond and Larry during the writing of the proposal. The collaborative proposalwriting project consisted of 33 of the total 71 episodes (47 percent). Audience concerns
accounted for almost 50 percent of the episodes and references to the need for alternative
research plans occurred in almost 30 percent of the episodes. The following excerpt
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exemplifies the interaction between the writing of the proposal and the direction of the
proposed research:
Larry: 1 We did a copper test which was completely lost. 2 I was telling
you about the quality and so on. 3 By the time we were ready to do the
experiment we found out that it wasn’t set up right. 4 So we’re definitely
going to have one day.
Raymond: 5 Okay, yeah, shit happens. 6 The discussion of the IMAC
results needs work. 7 Then I tried to build a transition between the DSC
stuff, so this is sort of a new paragraph I put in. 8 It’s basically based on
the primacy of the IMAC results; however, it was necessary to assess the
affects of the preliminary protein structures. . . . 9 So this is like, we’ve
got a protein, drop it in that window, and the IMAC activities studies of
those proteins would probably show whether the strategy’s working or
not, and close the picture. 10 The thing I’ve been stressing in the DSC
surface localization. 11 And so let’s see if we can perhaps detect
localization in the DSC, localization binding if possible. 12 To do that,
we could do DSC experiments. 13 We’ve seen all this before; it’s pretty
helpful. 14 The only thing I took out was, I took out the isothermal stuff
because the entropy technique does it anyhow. 15 That’s why I created
the appendix; extending methods to be employed. 16 Strategies,
rationales. 17 So, okay, first let’s choose model proteins and then I tried
to do something with the characterization model. 18 Which is DSC kind
of shit. 19 Fractionation stuff. 20 Then metal-binding studies (Taped
meeting).
A discussion of a failed experimental trail (sentences 1, 2, and 3), evolves into a
discussion of which experiments the two biochemical engineers need to carry out and how
they should write them into the proposal. Raymond points out several parts of the
proposal that need to be improved (sentence 6) and describes a transition he has built
between Larry’s IMAC section and his own DSC section (sentences 7 through 11). In sentence
12, he explains the usefulness of the DSC experiments in the context of the proposal’s
argument and, in sentences 14 through 16, he gives his rationale for moving the isothermal
data-collection technique to an appendix. Finally, in sentence 17, Raymond identifies
their need for a definitive list of model proteins.
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Table 7 of Appendix G shows the percentage breakdown of activities performed by
the biochemical engineers during the planning stage of the proposal-writing effort. The
planning phase of the collaborative project made up 24 of the total 33 episodes (73 percent).
However, the writing/revising phase, as pointed out earlier, was not represented by the 33
episodes. Again, rhetorical considerations dominated the episodes (71.5 percent) as well
as considerations of how the audience might react to the proposal (12.5 percent). One of
the most significant outcomes of the planning sessions between the two collaborators was
their establishing an agreed upon number and type of model proteins and discovering an
effective means of presenting that information in the proposal:
Larry: 1 The reason I’m picking galactosidase is because, from my point of
view, we can say that we already have these [other proteins]. 2 So it
won’t look like we haven’t decided what to do. 3 So, I don’t know, are we
going to have tails for each of them attached, or. We can do it. 4 We can
do five or six different proteins like that. 5 In terms of IMAC that will
take us a while to figure out what’s happening. 6 Especially if we get
good mutations of the cysteine we want. 7 Because we have already
established that we can do that. 8 We have too many model proteins
now, that’s the problem. 9 It’s not a problem, but it’s how we want to
justify each . . . variant and for what reason we’re doing it. 10 I can make
a case in terms of IMAC. 11 If we show, in terms of IMAC, because it’s
important and also what is the distribution of each of these. 12 In short,
I would generate a number of proteins which a different degree to which
we can qualify those with IMAC. 13 Residual binding to no binding.
Raymond: 14 I guess the problem is, we need a matrix or a table or
something. 15 That would work a lot for progression, know what I mean?
Larry: 16 Yeah, something like that would put everything in
perspective. 17 These are only two cysteines and we are going to make
mutations (Taped meeting).
The rationale for choosing to study galactosidase is based primarily on pragmatics;
that is, the biochemical engineers elect to study certain proteins either because they have
access to them (sentence 1) or because the proteins will produce the effects they expect to
use in the proposal’s line of argumentation (sentences 6 and 7). Larry, however, realizes
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that they were in danger of complicating the proposal by using too many model proteins
(sentence 9) and recommends that they may need to defend their use of several proteins
(sentence 9). He then characterizes how he would defend the model proteins used in his
section of the proposal (sentences 11 to 13). Finally, in sentences 14 and 15, Raymond
recommends that they represent their model proteins using “a matrix or a table or
something,” a suggestion that Larry agrees with in sentences 16 and 17.
Two important issues are revealed by this exchange. First, the proteins that the
biochemical engineers selected for study were chosen, not only because they were of
inherent interest to the scientists, but also because they were readily available. And
second, the decision to represent the model proteins in a table, made during the proposalwriting effort, would eventually inform the biochemical engineers’ experimental approach
and their eventual journal writing (by providing them with a matrix to basically “fill in”).
Table 8 of Appendix G shows the activities that Raymond and Larry engaged in
during the evaluation stage of the proposal-writing project. The evaluation phase of the
collaborative project consisted of 9 of the total 33 episodes (27 percent). Notably, the
biochemical engineers stressed how the proposal-writing activity influenced their
research activities (33 percent of the total episodes). In the following excerpt, Raymond
describes the difficulties that he and Larry encountered during the writing of the
collaborative proposal:
Raymond: 1 What slowed us down was, we got to the point where we had
the master document, and I thought my sections were reasonable and his
were okay, but we got those two things that kind of bogged us down. 2
One was relevant to me, the other was relevant to him. 3 And that was
the definition of a set of model proteins. 4 You know, trying to work that
out as you’re writing. You’re writing. Think about it. 5 And we just had a
tremendous problem defining a logical set. 6 You know, let’s choose ten
model proteins. 7 Why we chose them? 8 Why are we working with
them? 9 What do we expect to see with them? 10 What they’re going to
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give us? 11 And likewise, at that time, I had two possible
interpretations of some of my results, which didn’t have an impact on the
proposal as far as the techniques I wanted to use being useful, but I was
kind of fighting with those. 12 I worked out a better interpretation, and
then we got together and made that table there on that blackboard. 13
And we talked about it, and suddenly had this idea of the table, and
found a set of things to work with, and went back and wrote our sections
more around that thing. 14 Merged them again. 15 But that slowed us
down. 16 That was like, really working on a research plan. 17 Sort of
like, attacked by an inert proposal, so, take a break. 18 Go in, fix things
up (Open-ended interview).
Raymond emphasizes how important it was for them to establish a set of model
proteins. Moreover, he lists a (well-learned) series of questions that their proposal will
need to answer about their choice of model proteins (sentences 6 through 11): “Why we
chose them? Why are we working with them? What do we expect to see with them?
What they’re going to give us?” In addition, Raymond re-counts the importance of the
table for their proposal’s organization (sentences 12 and 13). And he concludes by stressing
the crucial influence that the proposal had on their research plan: “[Writing the proposal
was] really working on a research plan. [We were] sort of . . . attacked by an inert
proposal” (sentences 16 and 17). Finally, all these issues point to the high interaction
between their representation of the audience for the research proposal and the ultimate
direction that the research plan took; that is, in defining their research plans, the
biochemical engineers could not, if they expected the proposal to succeed, ignore the review
panelist’s opinions, reactions, and criticisms toward their “documented” plan.
In the next section, I outline the analysis of Raymond’s initial proposal-writing
effort which occurred shortly before Raymond and Larry began the intense collaborative
effort described above.
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Raymond’s Initial Proposal-Writing Effort
The first proposal-writing project consisted of 15 episodes out of the total 71 (21
percent). Interestingly, unlike the collaborative proposal-writing project, Raymond’s
initial proposal-writing effort included no references to audience considerations. It may be
that, when working collaboratively, the biochemical engineers were compelled to
articulate more about the intended audience for their proposal. Or, it may be that,
working in isolation on his proposal reduced the amount of effort that Raymond put into
defining and anticipating his potential audience.
Table 9 of Appendix G represents the activities that Raymond carried out during
the writing of the first proposal. Only one episode in the first proposal-writing project
contained references to Raymond’s planning process. This is most likely a result of the fact
that the data collected about the first proposal project came from talk-aloud protocols and
discourse-based interviews, all which tended to emphasize revision and evaluation. As
pointed out earlier, the talk-aloud protocols were an excellent source of information about
the biochemical engineer’s writing/revising strategies, whereas the discourse-based
interviews tended to elicit evaluative strategies.
Table 10 of Appendix G outlines the analysis of the writing/revising stage for the
initial proposal-writing effort. Eleven episodes out of the 15 (73 percent) were of Raymond
as he revised his proposal. In revising his proposal, Raymond referred frequently to goals
of “making it interesting,” “finding a good angle,” and “covering his butt.” In the following
excerpt, for example, he stresses finding an organization for his argument and building a
convincing justification for his data collection techniques:
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Raymond: 1 In reading over the other paragraphs in this section, it
strikes me that the logic here has to be turned around here. 2 It’s
probably better to talk about what we do in terms of the pressure
spectrum, which is a much different organization than’s here right now.
3 So we start moving paragraphs around, and the idea has occurred to me
that we’ll be getting some information out of this that might be a bit
more quantitative than we can get from the calorimetry techniques, and
that means I can build in the idea that this is an independent method
getting towards the answer that we’re after. 4 But also it’ll give me some
information that I can’t obtain any other way. 5 Which will give us sort
of a unique angle and better justification for the use of the high pressure
techniques (Talk-aloud protocol).
Raymond is well aware of the contingent nature of his science. As he states in
sentence 2, he also understands that there are certain advantages to stressing one particular
data-collection approach (pressure spectrum) over another (calorimetry techniques)
because the former will provide him with more quantitative results (sentence 3). He
concludes by pointing out that this revision will strengthen his argument by doubling the
number of independent methods used to observe the phenomenon (sentence 5). Indeed,
Raymond’s revision processes are often very strategic and rhetorical:
Raymond: 1 So in revising this section here, it’s probably about the same
length as the section was originally, but it now contains a little more
background information, which demonstrates that we know what we’re
talking about and what we hope we can get done. 2 And it accomplishes
this [reference to the need for a] facility at the University of XYZ. 3 And
the only thing that we might need in the future, or this proposal might
need more of is some mathematics and some theoretical frameworks to
throw in, which would probably make it a little harder to read, but it
might be useful to put some of those things in, in any case, just to show
that we can use the theoretical frameworks out there as data analysis
tools (Talk-aloud protocol).
Sentence 1 reveals Raymond’s well-learned knowledge of scientific discourse
conventions; that is, he is aware of the importance of providing the necessary background
information in order to frame his potential contribution to the field. In sentence 2, he refers
to another rhetorical strategy, the reference to his wanting access to facilities located at
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the University of XYZ. As Raymond posits in another talk-aloud protocol episode, “I just
mention the keyword that this laboratory is an NIH resource and that it’s there for people
like me to go out and fool around at, and hopefully that will be a positive factor in the
reaction these people have to this section of the proposal.” Raymond concludes the excerpt
by suggesting that the proposal may ultimately need “some mathematics and theoretical
frameworks” which, despite making the document more difficult to read, should heighten
the proposal writer’s credibility.
In conclusion, although only four out of the 15 episodes (27 percent) involved text
evaluation, these episodes often revealed Raymond’s awareness of how proposals are
reviewed and evaluated, particularly in collaborative situations versus individual efforts.
Most importantly, Raymond states that reviewers often look for the proposal writers’
levels of commitment to other projects:
Raymond: 1 When you review a paper that’s collaborative, you tend not
to really notice the collaboration. 2 When you review a proposal that’s
a collaborative effort, you tend to take more note of it; that’s because you
want to ascertain, in your own mind, whether the collaboration’s
meaningful and what are the odds of it actually being able to take place.
3 Yeah, there’s a real reinforcement going on. 4 People do look at that. 5
Especially really big proposals. 6 Especially NIH, where proposals tend
to be much bigger, more money and personnel than NSF, and people will,
on the panel, look at that in the end, after they talk about the proposal.
7 You know, comments like, why’s so and so written into this thing; he
doesn’t seem to be doing much, and that would take 200k off the budget or
something. 8 So, and the comments that the reviewer would get back
would be, not necessarily those comments, they might be an overall
reduction in the budget and kind of leave it up to the PIs [Principal
Investigators] to decide who gets axed (Open-ended interview).
Raymond views collaboration in the proposal-writing process as distinct from
collaboration in journal-article writing (sentence 1); in addition, the size of the proposal’s
budget (sentence 5) and the funding agency being applied to (sentence 6) influence how
carefully the reviewers will attend to the collaboration. Finally, he emphasizes the
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contingent nature of a proposal’s success, stating that restricting the budget is sometimes one
way of limiting a proposed collaboration (sentences 7 and 8).
In the next section, I outline the results of the analysis of the journal-writing
project. In particular, I was interested in identifying any notable differences between
composing a scientific journal article and writing a proposal for research funding.
Raymond’s Earlier Journal-Article Project
Twenty-three of the 71 episodes (32 percent) made up Raymond’s journal article
project. All 23 episodes, it should be noted, came from the three open-ended interviews of
Raymond, and centered around two drafts of a journal article that he was about to submit
for publication.
Table 11 of Appendix G outlines the breakdown of activities described by Raymond
about the writing of his journal article. As with the two proposal-writing projects
described earlier, the episodes centering on Raymond’s journal writing contained numerous
examples of rhetorical sensitivity (73 percent). On the context for re-writing the original
draft of the article, Raymond described the following:
Raymond: 1 The focus of the research is what happened when these
things [proteins] were attached to membranes. 2 They had different
surface chemistry. 3 But along the way, we saw something interesting,
and because the focus was elsewhere, we did not, at that time we
thought, you know, we saw something interesting and we did not look at
it, we looked at it fairly extensively but, it, in itself, probably could
have been something that maybe should have been studied as a whole. 4
Rather than just, you know, there as chunk of an overall thing. 5 And so,
I think, to give the reviewer some credit, I think the extent to which
what we looked at and the ideas we had, which were really good and
interesting—most people kind of, nobody really argued with the
ideas—but there was the gap between what we had and the ideas we
had. 6 It was probably kind of wide. 7 You know the conclusions and the
claims we were making were based on the data, then they were based on
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my own editorial. 8 So that’s the original alignment. 9 And having
looked at it for about six months, and having done a couple of other
experiments last summer to maybe explore some of the positive comments,
positive in the sense that did you think of this, did you think of that
(Open-ended interview).
After explaining how their interest in protein composition evolved over time
(sentences 1 through 4), Raymond goes on to describe the reviewer’s response to his first
draft (sentence 5). As he had stated in other interviews, Raymond recognizes the
importance of couching his claims in his existing data; in sentence 5, for example, he
suggests that the reviewer’s problem with his article was that there was a “gap between
what we had and the ideas we had.” In sentence 7, Raymond further describes a major
shortcoming of his first draft when he says that although “the conclusions and the claims
we were making were based on the data,” they were also “based on my own editorial.”
Lastly, Raymond explains his strategy for responding to the reviewer’s comments; that is,
he identifies what he refers to as “positive comments,” comments which emphasize “did
you think of this, did you think of that.” These questions, in turn, appear to act as
heuristics for evaluating the first draft of his article.
Table 12 of Appendix G shows the breakdown of activities that Raymond described
as taking place during the planning stage of the article project (which accounted for seven
out of total 23 episodes). Five out of the seven, or 72 percent, of the planning episodes
contained some reference to rhetorical strategies used in writing the journal article; and
most of these references occurred in conjunction with references to the potential audience’s
reaction to the written article (58 percent):
Raymond: 1 So we went at it experimentally, we, you know, did some
partial scan experiments and all that. 2 They were convincing to us, but
then you need to, you have to show big bumps. 3 Your pictures have to
have big bumps. 4 So the bumps weren’t big enough. 5 So at that point
I’m there, well, what I can do is pare it down to a communication, send it
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in somewhere and say, hey, there’s something interesting going on here,
subsequent work will clarify this (Open-ended interview).
In this excerpt, Raymond describes how they carried out partial scan experiments,
but obtained disappointing results (sentences 1 through 3); interestingly, although the
results are “convincing” to him and his group, he is aware that the results will not convince
potential reviewers. His anticipation of the audience’s reaction to his pictures, in turn,
informs his (potential) strategy of using the results in a communication rather than in a
full-scale article (sentences 4 and 5).
Only one of the 23 episodes contained an explicit reference to Raymond’s revising
process:
Raymond: 1 And at first reading I figured that the differences between us
and them [another group working in a similar field] were mainly due to,
first, we treated the protein much differently and it’s kind of
inconsequential. 2 I should note that study when I go through and revise
this thing. 3 In fact, I went at this thing about three or four times, just
kind of revise it, where eventually my thinking has changed totally. 4
So now this is pretty much written. 5 All it needs is figure legends,
figures, and if we get that final result we’re looking for, slap that in, and
then it’ll go out before the summer starts (Open-ended interview).
This excerpt, again, exemplifies Raymond’s awareness of how his research “fits into”
existing research in the field. Although he realizes that his treatment of the protein does
not differ significantly from the treatment of another group of researchers (sentence 1), he
also recognizes the importance of acknowledging similar work (sentence 2). Also, this
excerpt emphasizes how Raymond uses writing to inform his on-going research plans; in
sentence 3, he describes how his “thinking has changed totally” during his revision of the
journal article and, in sentence 5, he reveals that scientific writing and data collection are
taking place simultaneously.
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The frequency of references to evaluating the journal article, made during the openended interviews, are reported in Table 13 of Appendix G. Evaluative references accounted
for 14 out of the 23 episodes (61 percent). Again, references to alternative rhetorical
strategies for producing the document dominated Raymond’s discourse (78 percent), as well
as references to potential audience reactions to the article (64 percent). In particular,
Raymond explicated the important role that the review process played in his writing of
the second draft of the journal article:
Raymond: 1 Okay the enzyme we’re working with’s a pretty technical,
useful enzyme. 2 It’s used for analytical applications, a lot of it’s sold. 3
It’s an unstable enzyme, so anything we learn more about it might be
useful to people that attempt to come up with ways of stabilizing their
enzyme preparations. 4 And so that’s sort of our original mind-set; went
through, wrote it up, sent it in. 5 And, as it turned out, one review was
pretty positive, the other was semi-hostile. 6 We probably could have
just revised it and sent it back in (Open-ended interview).
Beginning with a description of the enzyme he is studying (sentences 1 and 2),
Raymond goes on to describe why he feels other researchers will be interested in its study
(sentence 3). Although the reviews are both positive and negative (sentence 5), Raymond
and his collaborators decide to take a new approach to presenting their data. In the
following excerpt, he expands on the pragmatics and the usefulness of the reviewers’
feedback:
Raymond: 1 My sense was that what we did might come kind of close to
what somebody else was doing or they felt it was their area so it might
have been an intrusion. 2 In fact, one of the comments said why don’t you
use NMR and when I read that that kind of tripped in my mind a very
narrow number of, a very small number of possible people that reviewer
might have been.
Interviewer: NMR?
Raymond: 3 NMR being a technique that one can go in and assess what’s
going in and assess what’s going on in the protein structure. 4 And that
review was good, . . . it raised some interesting questions that we might
have just been able to argue around and neglect, but it also gave an old
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reference that we never found in the literature. 5 A very crude way of
doing these kind of experiments too (Open-ended interview).
This excerpt is particularly illuminating in that it highlights the political nature
of the review process. In sentences 1 and 2, for example, Raymond suggests that one of the
reviewers might have taken a proprietorial stance against his article. As well, the
sentences reveal Raymond’s acute familiarity with a specialized group of researchers
doing similar work. Importantly, he is not particularly surprised by this proprietorial
element of the review process and, in sentence 4, goes on to describe the review as “good” in
that it provided him and his team with a reference that turned out to be very instrumental
in the subsequent re-write of the article. The review process, then, places researchers in a
context where they are asked to both contribute and conform to the existing beliefs, norms,
and expectations of their discourse community.
To conclude, I would like to examine two excerpts. In the first excerpt, Raymond
characterizes his re-write of the drafted journal article, revealing his awareness of both
his rhetorical strategies for presenting his findings and his potential audience’s reaction to
his argument:
Raymond: 1 So we’re attacking ourselves again, but by looking like we’re
attacking ourselves, we’re leading up to the explanation I like the best. .
. . 2 So by attacking ourselves first and using what other people have
said to be aware of, we’ve tried to trash our own interpretation. 3 What
we do, we offered the bare minimum interpretation at the first, and by
trashing different alternatives kind of led to what I kind of like. 4 See,
in this I was very careful when I said it. 5 If somebody were to read this,
they’d have to go back and read again. . . . 6 A lot of things, keep it
general. 7 And as I kind of trash the alternatives, I get down to
something specific, rather than beginning with a hypothesis and saying
here’s something crazy that I’ve found. 8 I give the audience something
to chew on, then I give them something, well, you know, we’ve looked it
and it’s not an impurity and, in the beginning, everybody will probably
say, okay okay, and I could end at the domain thing and probably get
people to buy it. 9 And not do anymore, just end it there. 10 But I trash it.
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Interviewer: Why?
Raymond: 11 Because I don’t totally buy it either. 12 I’m trying to be kind
of honest in this whole thing. 13 I don’t totally buy it either. 14 It works
beautifully. 15 But, yeah, I don’t totally buy it. 16 So where we finally
end up now is we say basically that it’s probably, it could very well be
both things. 17 All right (Open-ended interview).
Raymond describes how he frames his argument or explanation in terms of
“attacking ourselves” in sentences 1 and 2. However, as he points out in sentence 3, his
original interpretations are predictably problematic. In sentences 4 and 5, Raymond refers
to the potential audience reaction to his line of argumentation and, in sentence 7, he
describes how he has deviated from the traditional problem-hypothesis-solution format
and, instead, started with a general overview of the issues and moved progressively
towards specific issues. Then, Raymond turns again to audience concerns (sentence 8), and
explains how he expects to extend his argument beyond the stage where they would
“probably . . . buy it.” His rationale for doing so, he posits, is that although his
explanation “works beautifully” (sentence 14), he does not “totally buy it either”
(sentences 11 and 13). He concludes the argument by suggesting that the domain and
heterogeneity perspectives towards enzyme structure are not necessarily mutually
exclusive notions (sentences 16 and 17). In another excerpt, Raymond explains that this is
often how he constructs a scientific argument: the “safe part” of the article is the
introductory, background material, the “core . . . that’s very difficult to attack,” and the
“speculative part” consists of the assertions that Raymond ultimately wants to make
regarding the structure of the enzyme.
In the next section, I elaborate on the 14 drafts that I collected of the collaborative
proposal. While the previous sections emphasized process information from the various
interviews and talk-aloud protocols, the next section emphasizes product information
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integrated with process information from the taped meetings and numerous notes exchanged
between the two biochemical engineers over the duration of the project.
Managing the Collaborative Proposal Project
The Fourteen Proposal Drafts
As described earlier, the collaborative proposal that Raymond and Larry wrote
over a three-week period of time was actually the result of discussions they had dating
back to March, 1990. Several months later, Raymond wrote up a five-page prospectus, but
until the RFP was announced by NIH in September, 1990, Raymond and Larry had
basically continued to run separate experiments, consulting each other informally about the
relationship between their various results. Late that summer, they designed several
mutual experiments, which ultimately informed their initial collaborative effort.
Their proposal, in short, involved the characterization of a type of affinity
chromatography, IMAC, with two complementary goals: (1) as a means of purifying
proteins and (2) as an analytical tool for characterizing metal-binding proteins and
peptide-metal interactions. To accomplish this, they proposed to construct a family of
model proteins using site-directed mutagenesis and gene-fusion techniques. It was their
hope that, in removing bound metal ions from these proteins, the elution profile of the
proteins would provide them with information about zinc binding and non-binding proteins.
In addition, their goal was to assess whether proteins with multiple-binding sites utilized
particular sites or multiple sites. Finally, they intended to characterize the model
proteins and to contrast them with the metal-binding behavior of engineered versus native
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proteins. To do so, they proposed to use numerous chemical engineering techniques: DSC,
light spectroscopy, CD spectroscopy, and metal-binding studies.
Table 14 of Appendix G presents the syntactical evolution of the 14 proposal drafts
(see, also, Appendix H for the chronology of the 14 proposal drafts). What is useful about
Table 14 is not only the differences across the drafts but also the similarities. Despite the
generation of over 500 sentences in three weeks (almost 10,000 words), Raymond and Larry’s
numerous drafts are extremely consistent in terms of word length—ranging from 1.6 to 1.8
syllables per word—sentence length—ranging from 19 to 25 words per sentence—passive
voice constructions—ranging from 25 to 37 per draft—and prepositions—ranging from 2.5 to
3.5 per sentence. The average paragraph length, with the exception the eighth and ninth
drafts, ranged between four and seven sentences per paragraph (drafts eight and nine
contained text that Raymond had downloaded as a computer file from Larry and that
contained no paragraph divisions; in draft 10, Raymond and Larry added paragraph
breaks and transitional sentences).
The development of the proposal, then, is marked by a consistency that suggests
that the biochemical engineers were employing a very well-learned set of writing
standards to the new text they created. That is, although the writing effort spanned
numerous days and drafts, and was a collaborative effort, the syntactical development of
the proposal was remarkably stable.
The finished proposal contained the following sections and subsections:
(1)
Specific Aims;
(2)
Significance (IMAC Background and Literature Survey, DSC Background
and Literature Survey, and Contributions of the Proposed Research);
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(3)
Preliminary Efforts (Zn (II)-IDA IMAC Experiments, Cu (II)-IDA IMAC
Experiments, Discussion of the IMAC Results, Overview of DSC
Experiments, DSC Results, Discussion of DSC Results, and Summary and
Anticipated Utility of DSC Studies);
(4)
Proposed Research: Materials and Methods (Organism E. coli, Protein
Isolation, Protein Assays, Gel Electrophoresis, IMAC Chromatography,
Site-Directed Mutagenesis, Gene-Fusion Techniques, and DSC);
(5)
Research Plan (Choice and Construction of Model Proteins,
Characterization of Model Proteins, IMAC Experiments, Metal-Binding
Studies, and Collaborative Arrangements and Time-table)
(6)
References; and an
(7)
Appendix: Expanded Methods and Prior Work (Gene-Fusion Techniques
and Site-Directed Mutagenesis).
Table 15 of Appendix G shows the development, over the three-week writing
period, of the 14 drafts. The table is organized simply to represent the percentage, in
words, of each section of the proposal—the specific aims, significance, and so on—as it
evolved over the 14 drafts. Some sections were revised numerous times throughout the
process, however the changes were not substantial enough to increase the overall
percentage of that section. The Specific Aims section (see Appendix I), for example,
although it was altered continually over the three-weeks, generally made up less and less
of the total percentage of the proposal as more text was added to the remaining sections
(from 15 percent to 7 percent).
Table 15 reveals two particularly interesting aspects of the collaborative proposal
project. First, it points to a problem that Raymond and Larry encountered early in the
project. The first draft of the proposal consisted of numerous (previously drafted)
paragraphs cut and pasted into a single file. However, the majority of the text was
removed (excluding the Specific Aims section) from the second draft (almost 84 percent of
the original paragraphs). Also, 11 percent of the second draft’s paragraphs were new (a
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first draft of the Significance section). In this respect, although the first draft gave the
two biochemical engineers a starting point for the project, very little of it was salvaged in
the second draft. The second trend revealed by Table 15 is the order in which Raymond and
Larry wrote the proposal. With the exception of the Research Plan (draft five) which
they started writing before the Proposed Research (draft seven), all of the other seven
sections of the proposal were completed in a linear fashion. Despite their linear revision
strategy, however, Raymond and Larry did revise the entire document thoroughly and
continually (unlike Selzer’s, 1983, study of the composing processes of corporate engineers
where the engineers revised little if at all).
Appendix J further elaborates on the percentage breakdown of the 14 draft
proposals, giving details of the Significance, Preliminary Efforts, and Research Plan
sections of the written proposal. In the next section, I take a detailed look at the evolution
of one section of the proposal, the Specific Aims section, and discuss how Raymond and
Larry revised and edited it over the 14 drafts.
Writing and Re-writing the Proposal’s Specific Aims Section
Appendix I shows the evolution of the Specific Aims section of the collaborative
proposal. The first draft, dated Monday, September 10th, consists of eight research aims.
The list also contains two notes that the authors intended to answer later, the first
attached to the fourth aim regarding crosslinking:
Is this protein crosslinked? If so we might want to look at reduced and
oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe
answer this question (Note on first draft).
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The second note follows the fifth aim and is a note from Raymond to Larry reminding him
“to look at finger literature to see what has been done on this topic or eliminate if you
think these experiments are not really feasible” (Note on first draft).
The second draft, dated Tuesday, September 11th, is changed substantially. The
first, second, and third research aims have been deleted, and two minor revisions have
been made (the addition of the missing noun, “cysteines,” to the seventh aim, and the
capitalization of the verb, “perform,” although they misspelled the word in the re-write).
In the third draft, completed two days later, the revisions are again quite local. In the
third research aim, they change the second sentence from “Determine, for example, if the
presence of the added fragment can suppress the effects the metal ions have on the
enzyme’s endotherm due to the fragment being able to bind the metal ion preferentially,”
to “Determine if the presence of the metal-binding, terminal fragment can suppress the
effects of the metal ions have on the enzyme’s endotherm due to the fragment being able to
preferentially bind the metal ion.” As Bazerman (1984, 1988) has pointed out, much of the
revising that scientists do is often limited to language refinement, which explains why the
biochemical engineers add the adjectives “metal-binding” and “terminal” to the noun
“fragment.” “Specificity,” in a scientific text is an important attribute. In aim four, they
extend the possible reasons for the existence of metal ion to include the secondary structure
formation and metal ion coordination and, in the fifth aim, they correct a minor
typographic error.
The Monday, September 17, draft of the Specific Aims section contained only two
local revisions—changing the typographical errors “difference amounts” to “different
amounts” and “Perfrom” to “Perform.” In the fifth draft, an interesting revision occurs: the
biochemical engineers re-incorporate the first three aims that they deleted from the
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second draft. Due to confusions over which draft was the “final draft,” many of the text
changes made to first four drafts appear to have been lost or re-incorporated in the fifth
draft (for this reason, the typos corrected in the last version re-appear in this draft).
There were no changes made to the sixth, Wednesday, September 19, draft.
However, the seventh draft contains significant changes. The note following the fourth
aim has been deleted, as well as aim five (and its attached note). And aims seven and
eight have been deleted. In the eighth draft, Raymond and Larry add a new first aim.
The aim of constructing and producing a family of ß-lactamases, moreover, was a direct
result of a meeting held prior to the revision (see next section for more on the two meetings
held between Raymond and Larry). In aim five, they change “DSC” to “Differential
Scanning Calorimetry (DSC),” since this is the first time the term is used in the proposal
and, in aim six, they add the techniques they will be performing on the ß-lactamases,
“IMAC, CD spectroscopy, and binding studies,” to the DSC approach.
Drafts nine and 10 contain only superficial changes. Draft 11, however, is
significantly revised. A new second aim is inserted after the first aim. This aim, as well,
was discussed during the meeting between Raymond and Larry, and emphasizes the
possibility of “alternative ‘window’ opportunities” resulting from their research. In the
second aim (which has now become the third aim), the awkward phrase “which are
without any” is replaced by the phrase, “that are devoid of.” The fifth aim, now made
redundant by the addition of the new, second aim, is deleted, and the last aim re-written
significantly. The engineered ß-lactamases are now described as model proteins (to insure
consistency throughout the proposal), the vague noun, “fragment,” is replaced by “tail,”
and the word, “tail” is further elaborated as a “tail being able to bind the metal ion
preferentially” (a more technically appropriate definition of the phenomenon they are
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describing). Draft 11 represents the most dramatic revision. Draft 12 contains an
additional, sixth aim, describing the IMAC procedure (which had been removed from the
fifth aim of the previous draft). And drafts 13 and 14 contain very few revisions: draft 13
contains a spelling correction, and draft 14 has the awkward phrase “exist via” replaced
by “can be generated by using.”
What the 14 drafts clarify about the revising habits of the two biochemical
engineers is that their strategies were varied and iterative. Some of the drafts were
revised significantly (e.g., drafts two, seven, 11, and 12) while others contained a few local
revisions (e.g., drafts three, four, six, nine, 10, 13, and 14). The only draft of the proposal
that was left completely untouched was the sixth draft. In addition, the only research
aims contained in the first draft of the proposal that still remained in the final draft were
aims one and two, although both were de-emphasized and moved to aims three and four.
As the next section will highlight, the various notes exchanged by the two biochemical
engineers and the two meetings they had to discuss the proposal were instrumental in
shaping the production of, not only the Specific Aims section, but the entire research
proposal as well.
Exchanging Notes to Aid Collaboration
Early in the proposal-writing process, the two biochemical engineers decided that
Larry’s IMAC experiments and results should dominate the proposal and that Raymond’s
DSC results should be used to support Larry’s findings. Hence the following note written by
Raymond and attached to the second draft of the Significance section:
Put in some DSC review stuff. However, seems that the main idea is
attempting to resolve which part of the molecule is involved with the
metal interaction and how the part can be altered? If this is the case,
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then more significance should be placed on the IMAC component and the
DSC review should mainly show competence? That is, I do not envision
proposing new theory although there may be room to do so in endotherm
deconvolution. This would be of the form of proposing reversible
microstate models (Raymond note to Larry).
The note exemplifies a strategy that the two authors would follow in subsequent drafts.
Also attached to the same proposal were reminders written by Raymond to himself to carry
out various activities. These included reminding one of his graduate students to search the
relevant literature (“Elizabeth, put in our literature values [ref for lit values]”),
questioning the need for more data (“Would it be worth running water-water, buffer/saltbuffer . . . to see if there is an exothermic CuSO4 ionization effect?”), and elaborating on
two possible hypotheses for explaining the same data:
Hypothesis 1:
1 Me(II) binds to unfolded state thereby perturbing foldedunfolded equilibrium toward the unfolded state. 2 The increased
availability of His and Trp in the unfolded state would be the driving
force.
Hypothesis 2:
3 Me(II) binds to native state and has a mild chaotropic effect
thereby lowering Tm and DH.
4 One can argue for #2: According to Smith the His is available
in chicken lysozyme. 5 Thus, unfolding lysozyme will offer no new His. 6
Also, lysozyme has Trp, but RNAase does not. 7 Thus, if Trp binding was
important and resulted in Tm decrease, then the effect should be greater
for lysozyme than RNAase because unfolding would offer a lot of Trp
only for lysozyme. 8 (SH is not a factor for either). 9 Also, the greater
amount of His in RNAase might allow for greater coordination number
and thus greater perturbation of native structure (10 Porvath shows that
high His proteins bind more strongly to IMAC columns and postulates
that His’s may be proximal thereby allowing for greater coordination). .
. . 11 Does other evidence exist for ME(II) binding resulting in an
alteration of structure?. . . . 12 The main hole is does unfolding expose
more His in RNAase. 13 Bovine RNAase has a total of four and the
Brookhaven databank should tell us where the Ne are.
The most notable aspect of the above note is also the most obvious one—that
writing had an on-going influence on Raymond and Larry’s process of interpreting their
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experimental results. Also, it is interesting to note that Raymond leans towards
hypothesis two because he “can argue for” it (sentence 4). The note is actually a collapsed
and highly condensed (or abstracted) version of a complex argument. In it, Raymond
acknowledges connected research (sentences 4, 5, 10, and 11), identifies a potential, causal
relationship (sentence 7’s “if-then” structure), eliminates possible variables (sentence 8),
elaborates on his interpretation (sentence 9), and identifies a potential problem with his
interpretation (sentence 13).
Other notes—the following attached to the Specific Aims section of the sixth
draft—stressed which parts of the proposal required additional work:
1 Now have some clean up of results and link between two results sections.
2 Appendix reduces length. 3 Next swat will expand proposed research
and clean up the text already there. 4 Will get feel for total length. 5
Thus, trim later and return to front to tighten up if possible (Larry note to
Raymond).
This note is particularly interesting in that, in it, Larry describes the multiple tasks that
have yet to be carried out; he refers to “cleaning” and “tightening” up the manuscript
(sentences 1, 3, and 5), addressing concerns about the length of the manuscript (sentences 2
and 4), building transitions (sentence 1), and elaborating on the existing text (sentence 3).
Figure 1 illustrates the significant changes that were made to the draft Larry is describing
(deleted text is stroked out and added text is underlined):
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Figure 1: A snapshot of the additions and deletions made to the introductory paragraphs of
the sixth draft. Underlined text represents text that was added to the existing draft and
stroked out text represents text that was deleted from the existing draft.
Although the first paragraph of the proposal remains untouched, the second and
third paragraphs are re-written considerably. Transitional phrases (e.g., “however” and
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“as a result”) are added to the text. Awkward phrases (e.g., “immobilized metal forms
additional coordination binding with appropriate solutes”) have been replaced by simpler
constructions (e.g., “the binding event”). The wordy “In an attempt to examine the
possibility of using. . .” is reduced to the phrase “To examine.” Their terminology has been
further refined to avoid misinterpretation; for instance, they replace the phrase, “few
proteins meet the structural requirement,” with “not all proteins have the amini acid
composition and structural requirements” and the word “metalloproteins” with
“metalloprotein content of B. coli.” They couch criticisms of existing research in a more
positive light. The sentence, “The IMAC as a tool for protein purification is only
understood in a very empirical sense,” for example, becomes, “However, despite the recent
promising technical developments in IMAC, its use as a tool for protein purification is,”
and so on. And finally, they have added references to issues discussed in other parts of the
proposal (the Methods and the Preliminary Efforts sections).
In the next section, I examine the two taped meetings held between the two
biochemical engineers and their influence on the plans made for writing the proposal and
on various drafts of the proposal itself.
The Two Taped Meetings
The biochemical engineers’ first meeting was held on September 21, 1990, for
approximately two hours. The conversation consisted of 212 turns, with the dialogue very
evenly distributed between Raymond (107 turns) and Larry (105 turns). Although I was not
present at the meeting, I collected copies of the notes made by both scientists. In general,
the focus of the meeting was on defining two particular enzymes in order to justify their use.
One of the enzymes was to have exposed His, whereas the other was to have two buried
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ones. Larry agreed to bring out these differences in his discussion of the choice of model
proteins, and Raymond agreed to cover the topic in his DSC Discussion and the BindingStudies sections. The use of the two native proteins was a key aspect of the proposal and
helped define the uniqueness of their strategy. Without it, the work still looked good to
the two authors but, in Raymond’s words, had “the appearance of a fishing expedition
that lack[ed] a coherent attack plan” (IMAC Proposal Meeting Notes).
Having defined the two proteins, the authors would then be able to show how
physiochemical characterization and molecular biology would be more effectively
combined in their research. As well, during the meeting the authors generated numerous
new “angles” and experiments: (1) they established some uncertainty about their
analytical chemistry approach; (2) they added temperature as a variable for the IMAC
and binding experiments; (3) they discussed the possibility of using metal loading as a new
variable in the IMAC, binding, and DSC experiments; (4) they agreed that pH had to be
included in the use of DSC in the experimental plan; (5) they noted the use of AA as an
analytical tool, and; (6) they introduced an additional data-collection technique into the
proposal. Their goal for the next version of the proposal was to “clean up the master” and
to “put in additional/alternative section headings so integration [would be] possible and a
coherent picture [would] result” (Raymond and Larry’s notes).
The purpose of the second meeting, held on Wednesday, September 26 (five days
after the first meeting), was to take stock of the progress they had both made since they
last spoke. The second meeting had two things in common with the first: (1) the amount of
turns taken by Raymond and Larry were remarkably balanced (96 and 97 respectively), and
(2) the topics covered in the meeting emphasized the technical issues surrounding the
writing of the proposal and the work yet to be completed on the project. Table 16 of
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Appendix G gives a breakdown of the planned tasks that Raymond and Larry established
during the two taped meetings.
In general, both meetings emphasized three broad types of task assignment: (1)
writing assignments centered around particular sections of the proposal, (2) writing
assignments dependent on the technical expertise of either Raymond or Larry, and (3)
discussions of administrative details. References to sections of the proposal made up 42
percent of the three assignments; references to writing based on technical expertise made up
40 percent of the assignments, and; references to administrative tasks made up the
remaining eight percent of the assignments. Importantly, all the assignments undertaken
by the two biochemical engineers were voluntary; that is, they were both clearly aware of
which sections of the proposal they each had the knowledge and skill to complete.
Interrater reliability, as I pointed out in Chapter 4, was not necessary for this part
of the data analysis since the assignment of tasks and the follow-up check to see whether
the tasks were, indeed, carried out were not difficult to interpret. An example will
reinforce my point. During the first meeting, while looking at page 21 of the proposal,
Raymond and Larry decided to add the possible effects of pH and tm to their Discussion
section:
Raymond: Ah, so I think then that this stuff would just add onto that.
Larry: PH effect, temperature effect. We can throw this in here.
Raymond: Yeah, down at the bottom. And start throwing in paragraphs
there. Then that section’s a little tighter. Right now, the way it stands,
you know, this work could be a thousand miles apart. That’s okay, but
it’s got to be a little more weaved together, in some sense (Meeting one).
In comparing the proposal draft dated before the meeting and the draft after the meeting, I
was therefore able to quickly establish whether or not the biochemical engineers had
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altered that section of the proposal. It is notable that all the tasks established by
Raymond and Larry during the two meetings were incorporated into the written proposal,
further support for my argument that both meetings were held at crucial planning stages of
the proposal-writing project.
Finally, the breadth of tasks discussed in the two meetings deserves some
attention. During the first meeting, Raymond took responsibility for 15 tasks and Larry
took responsibility for 11 and, during the second meeting, Raymond took responsibility for
seven tasks and Larry took responsibility for 10; indeed, the distribution of tasks divided
between the two biochemical engineers is remarkably balanced: 22 tasks carried out by
Raymond and 21 tasks carried out by Larry. This distribution is generally consistent across
all three task types, supporting the notion that the collaboration was very much a joint,
evenly-shared endeavor.
Limitations of the Case Study
In presenting the results of my analysis of Raymond and his colleague’s writing in
this chapter, I made a deliberate rhetorical decision to move the tables to an appendix for
two reasons. Because data were collected using numerous methods and because I had
actively selected excerpts from the enormous amount of data available to me, I felt it
would be problematic to assume that the percentages I described were not (at least in part)
a reflection of my research interest and research questions.
Both these issues clearly raise concerns about the generalizability of my study of
proposal writing in biochemical engineering, and I believe I have addressed some of those
concerns in Chapters 1, 2, and 3. Moreover, the types of questions driving my exploratory
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study of proposal writing (see Chapter 4), in general, necessitated my doing a detailed,
long-term case study of a single writer-scientist. I also recognize that it is impossible to
know which (if any) of Raymond and Larry’s writing strategies are peculiar to them as
individual writers, and do not necessarily reflect the writing practices of other
biochemical engineers. To this end, I feel strongly that my study compliments well
previous studies of the composing processes of academic and nonacademic writers in their
natural settings (e.g., Bazerman, 1988; Gilbert & Mulkay, 1984; Kaufer & Geisler, 1989;
Miller & Selzer, 1985; Myers, 1990; Rymer, 1988; Selzer, 1983, etc.).
In addition, because my study covered research activities and writing projects
spread out over two years, it is important to point out that my data do not represent a
“complete” picture of Raymond’s writing processes and products. Certainly, at least in
terms of the three writing projects, I was able to collect very detailed descriptions,
however, it would be naive to assume that my data do not omit numerous important reading
and writing events that shaped and influenced Raymond’s composing efforts (the NIH
review panel, e.g., has yet to inform Raymond and Larry of their proposal’s success or
failure at the time I am writing this chapter). As a result of the inevitable
“incompleteness” of my data, I have been very careful to avoid drawing causal conclusions
about the connection between the three writing projects (in fact, I collapsed and analyzed
them as a single statement about Raymond’s composing practices earlier in this chapter).
And I have also been careful not to characterize the collaboration between Raymond and
Larry as an ideal or representative one; indeed, they encountered numerous difficulties
during the project (e.g., keeping track of multiple versions of the proposal, hurredly
collecting data necessary for the proposal’s line of argumentation, wrestling with
conflicting hypotheses and how they should be presented in writing, and so on) that might
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ultimately form the basis of what collaborating researchers need to be careful to avoid or
to pay special attention to.
And finally, because I deliberately took as much of an “insider’s stance” as was
possible for me (given my limited mathematical and scientific training), it was sometimes
difficult to separate myself from the biochemical engineers’ motivations and actions. For
instance, one colleague, while looking at an excerpt I had labelled “Audience
Characterization,” emphatically declared, “my gawd, lots of things are going on in here,”
and convinced me that audience construction was, indeed, interacting with the scientists’
perceptions of the field’s literature, their schema for the literature, and their implicit
sense of what a scientific contribution entailed. Because I had acquainted myself with the
research articles being discussed by the two biochemical engineers, my reading in part
interfered with my ability to interpret their discussion about the potential audience for
their research proposal.
These issues—the exploratory nature of the study, my active involvement in the
on-going data-collection process, and the small n—represent limitations that should not be
ignored and yet, in part, were inevitable given the nature of the broad questions driving my
study. In the next section, I outline the general conclusions of the study, and set the stage
for Chapter 6 and my discussion of the implications of the study for researchers interested
in scientific discourse.
General Conclusions and Remarks
The questions driving my study of a proposal writing in biochemical engineering
were, essentially, (1) how do scientists plan, write, revise, and evaluate proposals written
145
for research funding, (2) how do they characterize the intended audience for their
proposals, (3) in what way do they anticipate audience reactions to their texts, (4) what is
the interaction between proposal writing and scientific research, (5) how do they integrate
existing scientific research into their texts, (6) what role do discussions of technical issues
and constraints play in the proposal-writing process, and (7) how rhetorically sensitive
are proposal-writing scientists?
The most significant, and recurring, finding in the study was that writing—at least
the writing done by Raymond for the field of biochemical engineering—is rarely, if ever,
done in isolation. Collaboration plays a crucial role in the scientific and technical
inscription process (cf., Latour & Woolgar, 1979; Olsen, 1989).34 Even when Raymond
described writing projects that, for the most part, he had written in isolation, he referred
to a “we” that consisted of graduate students, colleagues, researchers that were part of his
discourse community, administrative assistants, and so on.
34
That we have tended to emphasize individual writing efforts has been discussed by
numerous researchers interested in the role of collaboration in writing. Fearing
and Sparrow (1989), for example, argue that “instead of stressing the solitary
efforts of the writer to develop finely tuned prose, our textbooks and courses need
to teach students about organizational and group processes—to plan and manage
complex organizational writing projects, negotiate with team members, resolve
group conflict, and expect and deal effectively with the unexpected” (26). And, in
part, the lack of research on collaboration stems from our confusion about what
exactly it means to write collaboratively; for example, based on interviews with
24 technical writers, Debs (1989) argues that most writers do not realize how
much of their time is spent collaborating: “The majority of these writers at first
denied—sometimes vehemently—that they engage in collaborative writing; later,
after they had described the discussions and negotiations that go into the choices
they make while writing different manuals, they concluded, often with a statement
of surprise or reconsideration, that they do collaborate. In one case, of the eighty
text features discussed during the interview (including questions of audience, style,
and layout), sixty had been determined by the writer during discussions with
eighteen other members of the organization, yet initially this writer too had
responded that she rarely collaborates” (39).
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And perhaps it is the growing amount of collaborative research and writing in
science that has resulted in my finding that rhetorical strategies play a large role in the
proposal-writing process. Collaboration, after all, heightens the amount of talk about
texts and, in some ways, makes it easier for researchers interested in scientific discourse to
“capture” strategies as they occur (cf., Doheny-Farina’s, 1986, discussion of corporate
writing and his emphasis on two extended meetings held by the writers involved).
In addition to revealing the integral role that collaboration plays in the writing
process of a biochemical engineer, the study also undermines the popular myth that
scientific and nonacademic writers spend little time and energy planning, revising, and
evaluating their texts (Broadhead & Freed, 1986; Selzer, 1983). The amount of planning
invested in all Raymond’s writing projects accounted for 44 percent of the episodes I coded,
and the amount of text evaluation infused into the writing process accounted for 38 percent
of the episodes.
Notably, my study corroborates Bazerman’s (1988) and Myers’ (1990) assertions
that scientific writing and scientific research are interdependent activities. As Raymond
puts it, they “map onto one another” with the proportions changing depending on the goals
of the research scientist. Also, it is important to note that Raymond (and his colleagues)
altered existing research plans and directions more in the proposal-writing process (27
percent of the episodes) than in the journal-writing project (approximately 5 percent of the
episodes). As Kennedy (1983) has emphasized, it is not surprising that “Nothing
substantial has ever got done without someone proposing what he would do, how he would
do it, what he would do with it, how much it would cost, and how long it would take to do”
(124). It is my hope, therefore, that the study supports and extends Myers’ (1990)
147
contention that proposal writing is one of the most significant types of writing that
scientists do.
The study also follows Bazerman’s (1988) strategy of balancing between a
description of scientific discourse as cognitively driven while at the same time being
contextually constrained. As Debra Journet argues in her (1990) review article,
[That] science as a social construct which is, at the same time accountable
to empirical experience, is illustrated most vividly . . .
in the long case study Bazerman offers of Arthur Holly Compton’s
announcement of what is now called the Compton effect. Here Bazerman
shows not only the way Compton negotiates a knowledge claim, but also
how Compton is constrained in that negotiation by such things as his
theoretical commitments and existing research programs, the equipment
he uses, the data he turns up (165-166).
Raymond and Larry, as well, faced numerous constraints during the proposalwriting effort, the first being a shortage of time between receiving the RFP and the NIH
deadline for submission. Other constraints included their lack of familiarity with the
research that applied to their specific technical expertise, the RFP standards and
guidelines for submission, their awareness of the research interests of the (potential)
members of the review board, and so on; and all these constraints, in turn, motivated the
two biochemical engineers to find suitable solutions, to make and re-make research and
writing plans, and to revise and re-evaluate the proposal’s line of argumentation.
Finally, the study emphasizes the interaction between the writing processes of a
biochemical engineer and the texts that he creates (for publication and for research
funding). The business of science is, as Latour and Woolgar (1979) have argued, the business
of inscribing (or transcribing). Revising and re-thinking numerous drafts of scientific
writing, at least for Raymond, played a key role in his writing process as well as
influencing his research activities.
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In the next, and final, chapter, I discuss the implications of my study of a
biochemical engineer and his proposal-writing process. First, I discuss the role that
alternative methodologies played in providing different “windows” into the nature of the
proposal-writing process. This leads to an examination of a re-occurring pattern in my data
(and in the data of other studies of scientific writers, e.g., Gilbert & Mulkay, 1984, Rymer,
1988); that is, I argue that scientists use a storytelling repertoire to describe and discuss the
science they are writing about. Moreover, I explore the implications that the metaphor of
storytelling has for researchers interested in scientific proposal writing. Finally, I posit
that scientists (at least the two biochemical engineers I studied) are far more rhetorically
sensitive than we, in rhetoric and sociology, have tended to acknowledge. This, in turn,
leads to a call for research on the relationship between a rhetoric of science and technology
as argument and a rhetoric of science and technology as narrative.
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Chapter 6—Discussion and Implications
I think it’s going to be a classic study, and so I’m excited about writing it. .
. . I have thought about it. I sort of held it, oh like a little jewel in the
back of my head, uh, it . . . gives me a lot of pleasure just to think about it,
and the time is right. . . . It’s a beautiful story (interview with SubjectScientist S, 221).
Rymer, J. (1988). Scientific Composing Processes: How Eminent Scientists
Write Journal Articles. Writing in Academic Disciplines: Advances in
Writing Research, Vol. 2. D. A. Jolliffe (Ed.). Norwood, NJ: Ablex, 211250.
Putting it into words makes you think about it more than just doing things
(interview with Subject-Engineer, 280).
Winsor, D. A. (1989). An Engineer’s Writing and the Corporate
Construction of Knowledge. Written Communication, 6 (3), 270-285.
. . . I have heard a number of experimental psychologists say in response
to my chapter on the writing of their field, “the practices you describe
are not rhetoric; they are simply good science” (320).
Bazerman, C. (1988). Shaping Written Knowledge: The Genre and
Activity of the Experimental Article in Science. Madison, WI: The U of
Wisconsin P.
At its most general level, this dissertation has been about discourse in science and
engineering. The first chapter focussed on the role that research proposals play in the
dissemination and construction of knowledge in science, and relied on an adaptation of
Bazerman’s (1988) model of the complex negotiation that takes place between scientists,
their writing, research, and the funding agencies that support them. It was argued that
researchers interested in the rhetoric of science and technology need to better understand
150
the relationship between scientists, scientific research, proposals for research funding, and
the agencies that fund them.
Chapter 2 expanded on this discussion, and drew on literature from cognitive
science, academic and nonacademic research, the sociology and history of science, and the
rhetoric of scientific and technical discourse. After briefly characterizing the
contemporary scientific proposal writer, I outlined why the study of science (t h e o r i a ) and
the study of rhetoric (phronesis) have traditionally been separated. This lead to an
overview of the contemporary rhetorical interest in scientific discourse and, in particular,
highlighted the need for a rhetorical analysis of a genre that, to date, has received little
attention—the scientific research proposal.
In Chapter 3, I introduced two exploratory studies—the first, a protocol-based
study of fifteen technical and professional writing students as they composed short
proposals, and the second, an interview-based survey of the funding practices of fifteen
professional academics. Both studies represented useful starting points for my inquiry into
the general nature of the proposal-writing process, in that they showed how issues of
audience and tone influence the proposal-writing process, and how management and
organizational skills factor into the overall funding process. Importantly, both studies
also highlighted the need for a third study of proposal writing (described in Chapters 4
and 5), and suggested that the third study employ a myriad of data-collection techniques.
Using a case-study-based approach to studying writing in a scientific setting was,
for me, an important research decision. Rose (1985) has made a similar and convincing
argument for the same sort of departure from strictly qualitative or strictly quantitative
approaches to data collection. Describing the tension between writing researchers
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interested in a case-study-based approach to data collection and those interested in more
quantitative approaches, he writes
The naturalistic camp champions interpretation, rich detail, “thick
description,” while the more experimentally oriented camp insists on
measurements, numerical analysis, the discussion grounded in statistics.
The ideal text for the first group becomes the case study; for the second,
it’s the research article with its attendant tables and charts. But why
must these be the two primary choices—two extremes pitted against
each other? I would suggest that the most enlightening and
comprehensive writing about writing would fuse these two approaches,
would weave statistics into descriptions and provide interpretive human
contexts for measurements. We in composing-process research need a way
to write about our findings that blends the interpretive and metaphoric
with the baldly referential and notational. How else will we render the
richness of the writing act? (258).
As I described in Chapter 4, taking a Participatory Approach (PD) to data collection also
contributed to what I saw as an important need for multiple measures of the same writing
activities. The PD approach emphasizes the evolutionary and collaborative nature of
data collection, and stresses the need for studies of scientific writing that incorporate
scientific writers into the research process. In this way I have tried, in Chapter 5, to
“weave statistics into descriptions and provide interpretive human contexts for
measurement” in what I believe is a useful and convincing way (see Spilka’s, 1988, study of
six corporate engineers’ which bases its results on data collected using methodological
triangulation).
My goal for the third study, therefore, was to document, in detail, the proposalwriting efforts of a professional biochemical engineer over an extended period of time. In
particular, the following questions and issues required further investigation: (1) how do
academic writers represent or characterize the intended audience for their proposals; (2)
how does the proposal-writing process influence academic research plans or goals; (3) how
do academics anticipate their audience’s response to their proposals; (4) how do the
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discourse conventions of the field influence academic proposals for funding; and (5) how do
academic proposal writers integrate existing scientific research into their writing efforts?
Chapter 5, the results of the case study, confirmed many of my intuitions about the
role of proposals and proposal writing in scientific and technical settings. Indeed, my
findings undermined some of the myths that I believe we are currently guilty of
promulgating in the classroom, for example, “proposals are written before the research is
carried out.” Raymond, the biochemical engineer that my case study featured, and his
colleague-collaborator, Larry, for instance, were exceedingly audience-oriented. In
addition, their characterizations of the audience and anticipation of potential reactions
that audience might have to their writing influenced the amount of time and energy that
they spent weighing various rhetorical alternatives and problem-solving strategies. That
is, the biochemical engineers’ actively altered their research proposal’s subject-matter and
line of argumentation based on their sense of audience’s potential reaction to the text; thus,
they constantly referred to the need to “hedge,” “couch,” “omit,” “cover our butts,” “be
careful about,” “avoid getting nailed on,” and so on, throughout the planning,
writing/revising, and evaluation of their text.
My data (from open-ended interviews, discourse-based interviews, tape-recorded
meetings, and talk-aloud protocols) also support Greg Myers’ (1985b, 1990) assertion that
scientific research, journal-article writing, and proposal writing are highly
interdependent. In fact, the interaction between the writing process and the biochemical
engineers’ goals for the research was more intense in the proposal-writing project than it
was in the journal-writing project. A notable tension, between the feasibility (“safeness”)
of the existing data and the hypotheticality of their interpretations (“speculative
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editorial”), surfaced in numerous episodes, and appeared to play a major role in the writing
of all three projects.
The results also indicated that the two biochemical engineers spent a considerable
amount of time incorporating existing research literature into their texts. Notably, at least
for Raymond, incorporating research literature into his writing happened most frequently
in the revising episodes. In the planning and evaluation stages of the projects, he tended to
refer abstractly to “the work being done by other researchers,” and to how his research
differed or was similar to that research. In addition, both Raymond and Larry were
careful to present the work of others in a positive rather than in a negative light; this
finding, too, is discussed in the extensive literature on reference- and citation-use in science
and engineering (see, e.g., Gilbert, 1977).
Finally, Chapter 5 reveals the complex and social nature of the proposal-writing
process. Not only were Raymond and Larry engaged in a large, collaborative writing
project, but they were also negotiating numerous tasks with graduate students, technicians,
enzyme sales representatives, existing texts and technological platforms, administrative
staff, and with the perceived panelists who would eventually review their proposal.35
These interactions took various forms—exchanged notes, conversations in the hallway and
laboratory, telephone calls, fax machine correspondence, formal and informal meetings,
35
In fact, the negotiation over the written proposal goes well beyond the confines of
the time-period that I studied. After being submitted to the initial review
committee, the proposal would then be summarized by an NIH executive secretary
who would submit his recommendation for staff review. The staff reviewers
would then submit their recommendations to the national council of each institute,
who would, in turn, submit a final report to the institute’s director (see Murphy &
Dean, 1984, 1986). The proposal, of course, can be rejected at any level of the
NIH review process, although the initial review committee is the crucial hurdle.
154
computer mail, borrowed articles, figures and tables—all surrounding and incorporated into
the proposal draft as it evolved across the 14 versions.
In this chapter, rather than re-iterating the results of Chapter 5, I want to forward
several perspectives towards scientific proposal writing and the study of scientific and
technical discourse that have emerged from my study of a biochemical engineer and his
composing processes. The first perspective is that different methodologies for studying
proposal writing in science highlight different aspects of the overall process. What all
methods have in common, however, is that they emphasize the constructive nature of
research in the rhetoric of science; that is, researchers and participants are constantly
attempting to build plausible stories to describe their objects of inquiry. In this regard, the
second perspective holds that it is fruitful to view scientific proposal writing as a type of
storytelling or narrative. The third perspective is of scientific writers as rhetorically
sensitive or self-conscious. I define rhetorical sensitivity as the awareness, on the part of
the two biochemical engineers, of the contingent nature of their data-collection techniques,
their data, claims, and interpretations. Indeed, I believe a view towards scientists as
storytellers and scientists as rhetorically sensitive might have significant ramifications
for the teaching of both scientific writing and scientific reading. Thus, students might
benefit from instruction that bases itself in situated science stories, rather than from
generalized, isolated facts and lists.
Methods as Windows on Proposal Writing
Throughout this dissertation, when the discussion called for it, I have cited the
numerous studies that have called into question certain methodologies and their strengths
and weaknesses in terms of providing writing researchers with useful data for documenting
155
the complex processes of composing.36 There can be no doubt that any methodological
approach can be characterized as foregrounding certain aspects of a given process while deemphasizing other aspects, and this claim deserves some attention, given my goal of
applying multiple data-collection techniques to the study of proposal writing in science
and engineering.
At the most minimal level, any methodology can be said to have strengths and
weaknesses, particularly depending on the research questions one is attempting to answer.
In addition, various researchers have claimed that certain methodologies are better suited
to specific types of writing and particular contexts within which that writing takes place.
Table 1 outlines one way of viewing the influence that different methodologies have on
both the nature of the data collected as well as on the kinds of implications that can be
drawn from those data:
36
Although these references are cited throughout the dissertation, a condensed list of
pertinent readings includes the following: Berelson, 1971; Brenner, Brown, and
Canter, 1985; Brown and Herndl, 1986; Clifford, 1980, 1982; Cooper and
Holzman, 1983; Doheny-Farina and Odell, 1985; Ericsson and Simon, 1980,
1984; Garfinkel, 1967; Geertz, 1973, 1983; George, 1959; Gross, 1990a; Hayes
and Flower, 1980; Mulkay, Potter, and Yearley, 1983; Newell and Simon, 1972;
Odell, Goswami, and Herrington, 1983; Steinberg, 1986, and; Swarts, Flower, and
Hayes, 1984.
156
Methodology
Talk-aloud
Protocols
Disc.-based
Interviews
Open-ended
Interviews
Taped
Sessions
Written
Drafts
Exchanged
Notes
E-mail
Messages
Emphasis on
Cognitive or
Social
cognitive
Research(er)
Intrusion
Ability to
Quantify
high
excellent
Emphasis on
Process or
Product
process
cognitive-social
high
good
process-product
social-cognitive
high
poor
process
social
low
poor
process
cognitive
low
excellent
product
cognitive-social
low
poor
product-process
cognitive-social
low
poor
product-process
Table 1: Rough comparison of alternative methodologies and the perspectives they have
traditionally supported.
The above table is, of course, a tentative comparison of alternative methods and
the potential strengths and shortcomings of each given our goal of producing useful
descriptions of writing in science and engineering. Thus, for example, I have characterized
talk-aloud protocols as focussing on cognitive rather than social issues despite the recent
emphasis on categorizing the effects that different task environments have on our writing
processes (cf., Flower, 1989). And, similarly, I have characterized taped sessions as
emphasizing social issues, despite our ability to analyze them for examples of individual
agency and intention.
My rough characterization of differences between methods, however, is important
in that it highlights how applying multiple data-collection techniques can aid our goal of
constructing plausible stories about scientific writing. Indeed, data collected using
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different methods might uncover anomalies and conflicts in our representations of the
writing processes being studied (cf., Mulkay & Gilbert, 1984).
In the next section, I discuss the perspective towards proposal writing as
storytelling or narrative. My argument is that, just as rhetoricians of science translate
scientific behavior into stories for the members of their community, so too do scientists
employ a storytelling repertoire when describing scientific discourse and action.
Scientific Proposal Writing as Storytelling
Myers (1990) has stated that his major rationale for studying writing in biology
was to explicate the rhetorical nature of seemingly a-rhetorical scientific writing. In
doing so, he provides non-biologists with five strategies for reading and understanding
specialized texts: (1) Look for the rhetorical, (2) Reconstruct the social context, (3) Look for
related texts, (4) Look for the source of authority, and (5) Look for any links between
scientific language and everyday uses of language (255-258). In a sense, Myers is simply
asking non-biologists to “behave” like professional biologists when they read. Raymond,
for example, is reading the research articles of other scientists as arguments when he states
that he “doesn’t buy” a particular interpretation. And he regularly reconstructs the context
within which his research and the research of others takes place. Therefore, when he
disagrees with the same scientists’ conclusions, he is quick to add that it is because their
interpretation of the data have been “filtered by their research questions.” Similarly,
when Raymond receives the negative comments of one reviewer, he recognizes that the
comments might have had more to do with the reviewer’s personal research interests than
with his text. And finally, Raymond and Larry reveal an intense familiarity with other
texts and research activities of particular relevance to their research. That is, their
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proposal is “intertextualized” by an existing body of literature and “contextualized” by
their knowledge of the field.
Similarly, Bazerman (1988) turns his study of scientific texts to pedagogical ends
when he argues, “As teachers, if we provide our students with only the formal trappings of
the genres they need to work in, we offer them nothing more than unreflecting slavery to
current practice and no means to ride the change that inevitably will occur in the forty to
fifty years they will practice their professions” (320).37 His recommendation, therefore,
is to support “rhetorical self-consciousness” in the sciences and engineering. To do so, he
recommends the following guidelines: (1) Consider your fundamental assumptions, goals,
and projects, (2) Consider the structure of the literature, the structure of the community, and
your place in both, (3) Consider your immediate rhetorical situation and rhetorical task,
(4) Consider your investigative and symbolic tools, (5) Consider the processes of knowledge
production, and (6) Accept the dialectics of emergent knowledge (323-329).
As I discussed at length in Chapter 5, the collaborative project appeared to
heighten the amount of time and energy that the two biochemical engineers spent
explicating their research assumptions and goals for the proposal. In addition, their
discussions of the expectations of a largely “chemical” audience shaped how they
anticipated their proposal’s place in the existing research literature and the biochemical
engineering community in general. Finally, both Raymond and Larry—perhaps as a result
37
Wells (1986), too, has argued that our goal, as teachers of scientific and technical
writing, should be “to work within the structures of technical discourse so that
students can negotiate their demands but also be aware of the limited but real
possibility of moving beyond them” (264). This argument, of course, points to
the need for an approach to teaching that stresses both general writing skills and
particular discourse skills. That is, instead of confining our subject-matter to the
discourse norms of a particular field (e.g., physics, mechanical engineering,
biology, etc.), writing instructors need to emphasize how students can move
beyond certain constraints.
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of their “engineering” perspective towards biochemistry—spent a sizable amount of time
describing, elaborating upon, and discussing the data-collection tools that they would be
using. Triangulating the results of the numerous methodologies, therefore, prompted
numerous discussions about potential difficulties or unanticipated problems that they
might encounter.
My argument is a variation on the themes of both Myers (1990) and Bazerman
(1988). That is, it is my contention that scientists and engineers already employ what
Gilbert and Mulkay (1984) refer to as a contingent or informal repertoire to describe their
scientific research and writing, and that one instantiation of this repertoire is their
tendency to characterize scientific writing as storytelling. When we emphasize the
storytelling repertoire and its use by scientists, moreover, I believe that we begin to
recognize that scientists are already “rhetorically self-conscious,” to use Bazerman’s (1988)
term.
Myers, in his (1990) chapter, “The Cnemidophorus File: Narrative, Interpretation,
and Irony in a Scientific Controversy,” writes the following about his use of the term,
narrative, to describe scientific discourse:
By narrative, I mean the selection and sequencing of events so that they
have a subject, they form a coherent whole with a beginning and an end,
and they have a meaning that is conveyed by the sequence as a whole.38
If this seems an odd activity for scientists, it may be because we associate
narrative with storytelling, fictions, and falsehoods” (102).
Similarly, David Hamilton (1978) has pointed out that “Good writing . . . is always
carefully enacted and, in that sense, the qualification ‘scientific’ is hardly more
appropriate to writing physics than to writing stories” (32).
38
See also Freed and Roberts’ (1989) related discussion of “event sequencing” and
how we present narratives to describe our experiences.
160
When I argue that scientists use a storytelling repertoire to convey how their
research and writing evolve, I do not mean to imply that this strategy is peculiar to
scientists and engineers alone. Indeed, to one degree or another, we are all constantly
telling stories, creating and re-creating meaningful narratives. We only have to listen to
ourselves and to others as we describe a concert we have recently attended, a conversation
we have just taken part in, our rationale for applying to and attending a particular
graduate school, and so on, to realize that although each story consists of various “truths”
and “facts” (the concert was held at Carnegie Hall, the conversation lasted 15 minutes, and
the program we applied to was rhetoric), our opportunities for re-representing and recreating our stories are as plentiful as our imaginations allow.
What makes the storytelling metaphor so compelling when we are talking about
scientific discourse is that scientists have traditionally denied or hidden that aspect of
their process. This is not entirely surprising given its connection to rhetoric since, as Simons
(1989) has pointed out, “When ‘rhetoric’ is used in reference to scientists, textbook writers,
reporters, and the like, it is frequently a term of derision, a way of suggesting that they
have violated principles held high in their professions” (3). Hence the well-established
discourse conventions found in science and engineering (e.g., Gross, 1985), conventions which
actually reverse the sequence of events that many scientists go through when carrying out
scientific research. That is, scientific articles are generally designed to report, first,
existing research, an unanswered question (or questions), the methods used to answer the
question, the results of the study, and the implications for future researchers interested in
the question.
What my study and the studies of others (e.g., Bazerman, 1984; Collins, 1981a;
Latour & Woolgar, 1979; etc.) make clear, however, is that scientists rarely (if ever)
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proceed in this fashion. Indeed, it would be difficult (if not impossible) to produce an
effective review of the literature without first having some research question or interest
which drove that review, and it would be problematic to develop meaningful hypotheses
without first having some data (even anecdotal or intuitive) to guide your investigation
(see Schriver, 1989c, on the various strategies that empirical researchers use to “invent”
new theories and practices in rhetoric and composition).
Importantly, I am not in any way, re-iterating the argument that scientific texts
are therefore deceptive or misleading. Scientific texts have a distinguished historical
tradition and their design very successfully “forces” scientist-writers to negotiate between
their desire to “speculate” and the scientific community’s desire to “maintain” the
validity of existing theory and practice.
Fisher (1984) discusses what he calls the “narrative paradigm” in a manner that
appeals to me for this very reason; that is, storytelling, in Fisher’s (1984) view, is less
about fraudulence than it is about finding “good reasons:”
The presuppositions that structure the narrative paradigm are: (1)
humans are essentially storytellers; (2) the paradigmatic mode of human
decision-making and communication is “good reasons” which vary in form
among communication situations, genres, and media; (3) the production
and practice of good reasons is ruled by matters of history, biography,
culture, and character along with the kinds of forces identified in the . . .
language action paradigm; (4) rationality is determined by the nature of
persons as narrative beings—their inherent awareness of narrative
probability, what constitutes a coherent story, and their constant habit
of testing narrative fidelity, whether the stories they experience ring
true with the stories they know to be true in their lives . . . ; and (5) the
world is a set of stories which must be chosen among to live the good life
in a process of continual recreation (7-8).
162
The concept of “narrative probability,” or the search for coherence, is therefore not at odds
with our picture of scientific writing and research. And it does not turn the issue of how
scientist’s represent their research in writing into an ethical issue.
Journet (1990), too, points out how we tend to align storytelling with “fiction” and
scientific prose with “non-fiction:”
It may at first seem odd to associate narrative with science, as we
usually think of narrative primarily in connection with storytelling and
fiction. But theorists . . . now understand narrative more broadly as a
mode of interpretation common to factual as well as fictional writing. In
the act of constructing narrative, a writer imposes temporal and
sequential order on a mass of data by selecting and arranging
“significant” events. The writer’s decisions about how significant events
relate to one another, are the product of a particular theoretical
orientation or conceptual framework. Narrative is thus a way of
constructing knowledge that is important to any discipline that depends
on historical explanation, including geology and evolutionary biology
(164).
None of this changes the fact that, when we review the literature from the rhetoric of
science and technology, we still tend to be surprised when scientific writers are
characterized with traditional literary terms like “creative,” “imaginative,”
“resourceful,” “innovative,” and so on. Charles Bazerman, in his (1984) article, “The
Writing of Scientific Non-Fiction: Contexts, Choices, Constraints,” describes a scientist’s
writing process very much as though he were a fiction writer: “. . . by struggling with the
language the scientist writer can achieve a bit better fit between symbolization and
experienced world” (50).
Gilbert and Mulkay (1984), too, in their description of scientific writing,
emphasize the multiple choices that scientists have in representing “the reality” of their
research:
163
. . . the introductory sections of research papers, which often present
reviews of prior work and which to that extent are sources of historical
data, can be seen to be rather finely crafted reconstructions in which
certain kinds of events and actions are systematically excluded.
Thus, although we recognize that the history we constructed is
but one possible version of the history of the field, this “weakness”
cannot be remedied by relying instead on other kinds of data. Other
versions of the history will remain both possible and plausible (34).
Similarly, as with scientific writing, numerous researchers have also alluded to
the constructive nature of scientific reading. Gragson and Selzer, for example, in their
(1990) article, “Fictionalizing the Readers of Scholarly Articles in Biology,” show how
skillfully two biological articles construct a presumed audience and point out that this
“reveals how self-consciously rhetorical are both performances (including the one that
seems completely ‘conventional’)” (30) [italics added]. Their argument is influenced by
Walter Ong’s (1975) stance that “The historian, the scholar or scientist, and the simple
letter writer all fictionalize their audiences, casting them in a made-up role and calling on
them to play the role assigned” (17).
Not only are scientific articles apparently “fictions,” but scientific graphics as
well. As Gilbert and Mulkay (1984) observe
It is not possible . . . to assess how far our respondents in general were
treating the fictional nature of pictures as intrinsic to the phenomena of
bioenergetics or intrinsic to the realm of pictorial discourse. What is
clear, however, is that the great majority of them, that is, twenty out of
twenty-five, emphatically characterized pictorial representation in
their field up to the date of the interview as unavoidably speculative,
hypothetical, uncertain, interpretative, highly personal, and so on (155156).
164
As well, Myers (1990) has argued, not that scientific illustrations are conjectural, but that
they divert attention from the history which produced them and focus attention on “the
appearance and stories of the particular animals and plants studied” (159ff).39
So, too, is Raymond aware of the importance and usefulness of figures for
explaining his research (figures, i.e., with big bumps). During one open-ended interview,
for example, Raymond said that—given the time—he would have probably added more
figures; when I asked why, he said simply “to save words . . . people read and interpret the
pictures first.”
A closer examination of Jone Rymer’s (1988) study of Subject-Scientist J reveals how
extensively she employs the storytelling metaphor to describe his composing processes.
Seven out of the 27 excerpts that Rymer cites in the article (26 percent of the total cited)
refer to building a plausible story to describe the on-going research:
I usually take a most recent paper . . . so I’m making a start . . . the next
chapter of the story . . . you might as well say that we’re telling this
project and previously we had this, and now we have such and such
available method (interview with Subject-Scientist J, 220) [italics
added].
In the above excerpt, Subject-Scientist J characterizes each scientific paper that he
produces as another chapter in the book that is his research, with his “starting point” for
the next chapter rooted in his previous research project. In another excerpt, SubjectScientist J describes the pleasure he is having writing a current journal article:
This one is very special to me, and it’s not just because I want to add
another paper to my bibliography, but I think it’s very, very significant,
and I’m pleased with the way it came out . . . . I think it’s going to be a
classic study, and so I’m excited about writing it . . . . I have thought
about it. I sort of held it, oh like a little jewel in the back of my head,
39
For extensive discussions of the role and representation of images in science, see
Knorr-Cetina and Amann (1990), Lynch (1985), and Lynch and Woolgar (1988).
165
uh, it . . . gives me a lot of pleasure just to think about it, and the time is
right. . . . It’s a beautiful story (interview with Subject-Scientist J, 221)
[italics added].
It might be argued that Subject-Scientist J is not aware of the potentially
controversial nature of the phrase “beautiful story” as a description for a scientific
research article, but I would extend another interpretation. I would argue that he is aware
of the creative element of the journal-writing process and, further, that he prides himself
on his ability to “tell a good story:”
The pieces all fit together, and they . . . were fragments at the beginning,
and what’s interesting is that each section is almost an independent unit
in itself. And it’s like in biology, uh, ontogeny. . . . And so each section is
almost like a microcosm of the entire piece. So within each section I . . .
[am] looking for order, fitting it together, and then I’m really not sure
how the various pieces are going to fit together, so I work on the pieces . .
. and then I’m going to put it together (interview with Subject-Scientist J,
226).
The next excerpt highlights the role that “sequencing” or organization plays in SubjectScientist J’s perception of scientific writing:
I guess I had outlined in my mind prior to drafting five or six fundamental
points I knew I was going to hit. And this was one of them. . . . I did not
know the relationship; I didn’t know the order or the sequence. I’m still
not certain of the sequence. . . . It’s a starting point. There’s a logic to t h e
development of the story, and this just has to be in the middle or the end
(interview with Subject-Scientist J, 231-232) [italics added].
And, finally, J’s description of his writing process highlights his motivation to create an
“interesting” or “engaging” story, to “sell” his ideas to his audience:
Just isn’t catchy. Gotta sell the stuff. Doesn’t mean that you gotta be
dishonest. But it’s gotta be something that really catches people’s eyes,
so they stand up and pay attention (interview with Subject-Scientist J,
235).
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This means, in effect, that he has to present a compelling narrative (or “drama”)
describing his process of discovery:
. . . all at once I got a further insight. . . . I was talking about the problem
of heterogeneity . . . and then it suddenly occurred to me that the proteins
were not present in equivalent amounts due to variation in their content . .
. I hadn’t thought about that before, and it just strengthened the drama
of the study and so I wrote it in. This is the first time since I’ve been
writing this that something new appeared which I had not thought . . . I
had thought that most of the stuff was already in my head (interview
with Subject-Scientist J, 242) [italics added].
Rymer (1988) concludes her story/study with the following characterization of scientists
and scientific writing:
. . . scientist[s] are tellers of tales, creative writers who make meaning
and who choose the ways they go about doing so. As Subject J muses,
looking over his data and thinking about what it means to him: “I guess
the question I’m asking now is: How do you tell it? Do you tell it like it
is, or do you tell it like you predicted, or the story it makes, or what?”
(244).
As Rymer observes, her scientist “prepares himself for writing by immersing himself in his
story; what guides his writing, then, are his strong feelings and mental images about this
story he wants to tell” (232).
In conclusion, the storytelling metaphor for scientific and technical writing is
useful for several reasons. First, stories are always told by writers or rhetors and shared
with audiences or listeners. This emphasis, on the scientist-storyteller and his or here
scientific audience, in turn, highlights both the cognitive and the social dimensions of
scientific discourse production. Second, storytelling can be viewed as both a process- and a
product-oriented endeavor. The key is that all scientific texts must “place” themselves
within the stories that have gone on before them; they must adhere to Burke’s (1941, 1973)
notion of the “unending conversation” by refining, continuing, extending, altering, or
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clarifying the narrative that currently exists. Third, they give writing instructors who
teach scientific and technical communication another means of describing scientific
research and writing. The narrative form is, after all, a well-learned one, and having
students view their data collection, interpretation, and report writing as storytelling
represents a potentially productive place to begin. Raymond shows this inclination often,
when he describes certain aspects of his writing as “partly fictional,” “speculative,”
“interesting,” and so on. In Fisher’s (1987) words, “There is no genre, not even technical
discourse, that is not constituted by both logos and mythos” (85).40
In the next section, I outline a perspective towards scientific and technical writers
as rhetorically sensitive, and argue that sociologists and rhetoricians have generally been
guilty of “objectifying” scientists and the work that they do.
Scientists and Engineers as Rhetors
Jeff Goldberg, in his (1988) “Anatomy of a Scientific Discovery: The Race to
Discover the Secret of Human Pain and Pleasure,” describes John Hughes, a Nobel Prize
recipient for his research into the nature of endorphins, as follows:
To Hughes the pig brains were an absolute necessity. He needed a lot of
them, and here they were for free. He had tried explaining to the
butchers that he was looking for a chemical in those pig brains, a
chemical which resembled drugs derived from the opium poppy—a
natural “morphine” produced from within the animal’s own body which
might, someday, unlock the mysteries of safe relief for human pain. A
few of the butchers pretended to catch on, but Hughes quickly realized
that gifts of whisky and a little money proved more effective tools of
diplomacy than all his mad-sounding explanations (3) [italics added].
40
See, also, Steven B. Katz’s essay (1992) on narrative romance and the structure of
technical discourse. He recommends that, “In teaching students in science and
technology how to communicate to various audiences, . . . perhaps we should
teach them not only the language of experts and managers, but also the language
of public discourse, including the patterns of narration that permeate and constitute
our culture” (400).
168
It is this kind of description of the scientist, striving for fame, bent on discovering
truths as yet unknown, and armed with “mad-sounding explanations,” that permeates
current, best-selling accounts of scientific activities. And it is also this type of
representation that has resulted in our contemporary fascination with the business or
“drama” of science (cf., Nelkin, 1987).
Unfortunately, this perception towards scientists, scientific reasoning, and
knowledge has not been without its shortcomings. That is, in glorifying scientists we have
inadvertently marginalized the knowledge that we produce in the humanities and social
sciences, so much so that I regularly encounter humanists who are flatly distrustful,
antagonistic, or insecure about the relationship between their liberal arts concerns and the
“vocational” concerns of “a-theoretical” empiricists, technologists, and scientists. Because
I have worked with and studied colleagues in the sciences and engineering, and because I
have taught technical communication for engineering and technology, I am regularly
surprised by this perception of scientists and what they do. Indeed, it seems to me that
academic scientists spend a considerable amount of energy trying to teach their students
about the contingency of knowledge and the relative strengths and weaknesses of the
methods they employ to collect data.
In short, I am more often struck by the similarities I have (as a writing researcher)
with scientists and engineers, than I am with the differences. And I believe this
development is going to continue, given recent, “creative” interests in science and
mathematics such as game theory, simulation modeling, new physics, and so on. Scientists,
that is, are more and more motivated to “imitate” nature rather than to claim that they
are in the business of “discovering” it, and imitation is traditionally the province of
artists, musicians, and creative writers.
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Unfortunately, however, the die has been cast, and this, I believe, has resulted in
the portrayal of scientists and technologists as rhetorically naive or unsophisticated.
Researchers have claimed sociology, philosophy, and rhetoric as t h e i r “turf,” and
asserted that scientists and engineers have more to learn from us than we do from them.
Gross, for example, in his (1985) article, “The Form of the Experimental Paper: A
Realization of the Myth of Induction,” re-states a common conception towards
contemporary scientific knowledge-making when he writes: “The philosophy that acts as
scaffolding for the most sophisticated science is relatively naive, untouched by
contemporary developments in philosophy of science” (24). In his discussion of the
experimental research paper, a genre which “. . . satisfies a recurrent need to justify the
enterprise of experimental science in the face of the problematic nature of the inductive
processes on which that science relies for the creation and certainty of its knowledge” (16),
Gross (1985) further posits that “The philosophy of scientists is in fact at one with the
philosophy of the experimental paper, designed less to explore than to justify, designed to
perpetuate a myth, the myth of induction that will allow experimental science at all costs
to continue” (24).
Scientists, in this light, are not only philosophically naive, but they are also the
perpetuator’s of the myth of experimental ideology (a characterization made more
ominous by the phrase “at all costs”). As I described earlier in this section, I believe that
the development of this perception towards science is, in part, a reaction to our historical
deification of the scientific enterprise. But I also believe that it is an unproductive
characterization, and that a growing body of research in the sociology and rhetoric of
science and technology supports my stance. Many of the scientists interviewed in Gilbert
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and Mulkay’s (1984) book, “Opening Pandora’s Box: A Sociological Analysis of Scientists’
Discourse,” for example, reveal an acute awareness of the contingency of their arguments.
Speaking of the discourse convention of using the third person in science, one
biochemist observes:
1 Everybody wants to put things in the third person. So they just say, “it
was found that.” 2 If it’s later shown that it was wrong, don’t accept any
responsibility. 3 “It was found. I didn’t say I b e l i e v e d it. It was found.”
4 So you sort of get away from yourself that way and make it sound like
these things just fall down into your lab notebook and you report them
like a historian. . . . 5 Of course, everybody knows what’s going on. 6
You’re saying, “I think.” 7 But when you go out on a limb, if you say “it
was shown that” or “it is concluded” instead of “we conclude,” it should
be more objective. 8 It sounds like you are taking yourself out of the
decision and that you’re trying to give a fair, objective view and that you
are not getting personally involved. 9 Personally, I’d like to see the first
person come back. 10 I slip into it once in a while. “We found.” 11 Even
then I won’t say “I.” I’ll say “we” even if it’s a one-person paper. 12 Can
spread the blame if it’s wrong [laughs]. [Leman, 57-8] (58-59).
The third person construction, according to this scientist, has evolved as a means of
obscuring personal responsibility for the findings and for maintaining an “objective” tone in
scientific texts. He also contrasts this perspective with terms that we, in rhetoric,
regularly employ to describe the “reality” of scientific research and writing—I believe, I
think, we conclude, we found, and so on. And these discussions of the difference between
actual scientific practice and scientific reporting permeate Gilbert and Mulkay’s (1984)
interviews with scientists.
Another scientist, criticizing the way science is taught in school, characterizes
actual scientific practice:
5 One is a myth, that we inflict on the public, that science is rational and
logical. 6 It’s appalling really, it’s taught all the way in school, the
notion that you make all these observations in a Darwinian sense. 7
That’s just rubbish, this “detached observation.” “What do you see? 8
Well, what do you see? God knows, you see everything. 9 And, in fact,
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you see what you want to see, for the most part. 10 Or you see the choices
between one or two rather narrow alternatives. 11 That doesn’t get
admitted into the scientific literature. . . . [Spender, 32-3] (59-60).
Echoing sociologists and rhetoricians of science (Law & Williams, 1982; Mulkay & Gilbert,
1982a; Zappen, 1985; etc.), the scientist above is clearly aware of the differences between
scientific observation and the way it is presented in scientific literature; and, like
Raymond, he recognizes that interpretations and data are always, in part, a product of
what you are looking for. An ironic remark by another scientist reveals this perspective as
well:
Interviewer: 25 So the experimental evidence. . . .
Barton: 26 At the end of the day solves everything [general laughter]
. . . . [62-3] (96).
His laughter re-affirms, not that he is a “promulgator of the myth of the experimental
paper,” but rather the opposite; in effect, he is saying that experimental evidence does not
solve everything.
And finally, Cookson makes the most explicit statement of the contingent nature of
scientific knowledge:
. . . 11 Membranes are extremely complicated and it’s hard to know that
you’ve ever got the variables all pinned down, so that when in fact you
make an observation that that observation is really what you think it is.
. . . 30 What bothered me with this [alpha beta] episode was the final
and complete realization that there is no such thing as absolute truth. 31
I mean, last summer, it really hit me like a ton of bricks that truth is
simply what most people are willing to believe today. 32 And that’s
truth. 33 Tomorrow the population changes, people are not willing to
believe the same stuff that they were willing to believe the day before
yesterday, then truth changes. . . . [Cookson, 49] (104).
This excerpt, taken out of context, could well have been uttered by a sociologist or
rhetorician. In it, Cookson characterizes how undermining it was for him to realize that
172
“there is no such thing as absolute truth” and that “truth is simply what most people are
willing to believe today” (a worldview shared by most contemporary rhetoricians).
Certainly, not all sociologists and rhetoricians are guilty of portraying scientists
and engineers as rhetorically naive. Rymer (1988), for example, acknowledges the
rhetorical sensitivity of her scientists when she writes, “Subject K, echoing the
rhetoricians, social scientists, and philosophers of science, describes other scientists like
this:”
In writing papers, scientists go back and rewrite the history of the
experiment. . . . Eventually many of these scientists believe their own
rewriting and think that is the way they behaved, what they did.
They don’t recognize the accidents, the intuitions, the leaps of faith, the
sudden connections (interview with Subject-Scientist K, 241).
And Dorothy A. Winsor concludes her (1990) article, “Engineering
Writing/Writing Engineering,” with the following assertion:
Exertion of power through language is obviously not limited to
engineers. As I worked on this paper, I was uncomfortably aware that I,
too, was attempting to exert power. In particular, I am one of a group of
researchers outside technology and science who claim that scientists
have no special way of knowing unavailable to the rest of us. It seems to
me that in part we are reacting to the privileged position our culture
awards science and technology as ways of knowing. It is therefore likely
that we exaggerate the irrational aspects of science. As a scholar of
writing, it is great fun to say that engineers are actually writing about
other writing, a field I presumably know more about than they do. They
think their field, their way of knowing is superior? Nonsense! Their
field isn’t even their field; it is mine. But I also bow to privileged
scientific ideology by posing as knowing empirically with nothing
between me and what I see. Unmediated knowledge, however, is not
possible for any of us. All writing, including mine, constructs the world
which the writer can bear to inhabit (169).
This passage is particularly interesting (and playful) for several reasons. First, Winsor
recognizes that knowledge in engineering, as in the humanities, is not outside the province
of non-engineers. Second, Winsor is aware of the historical reaction to the “privileged
173
position our culture awards science and technology.” Third, she acknowledges that it is
doubtful that engineers are naive enough to believe that “their way of knowing is
superior.” And finally, Winsor reminds us that she, too, is “posing” as a scholar who is
able to empirically identify “truths” and “facts” about writing in engineering. I believe
this is a critical move on her part, and one that makes engineers and technologists less
“objects” of inquiry, and more “participants” involved in the debate over how knowledge is
constructed in the academy. In Raymond’s words, “Rhetoricians, social scientists,
biochemical engineers, whoever; we’re all basically in the same business—trying to account
for uncertainty.”
Implications for Research and Teaching
More than anything, my study of the proposal-writing process of a contemporary
biochemical engineer has highlighted the importance of methodological issues in writing
research. In Chapter 2, I outlined some of the reasons that protocol-based and interviewbased studies of writing fall short of answering all the questions we have about writing in
the sciences and engineering, and made a case for a naturalistic study of proposal writing in
one particular discipline. In addition, I explored the implications of a Participatory
Design approach for researchers interested in studying the processes and products of
contemporary scientists.
What my study has also emphasized is the need for extended, long-term studies of
scientific and technical writers. Only by immersing ourselves in the on-going research,
reading, and writing of individuals outside our discipline can we hope to better understand
and appreciate the opportunities and constraints facing them as they go about constructing
knowledge for their own communities.
174
Also, along with making a case for the critical role that proposal writing plays in
the scientific construction of knowledge, I have also discussed the difficulties that
scientists face when attempting to manage large, collaborative proposal-writing projects.
Proposal writing, in effect, is research planning and, as such, is a difficult and timeconsuming activity for scientists. Since my data are from two biochemical engineers writing
a proposal for the NIH, it is my hope that other researchers will extend my analyses to
other disciplines and to other funding situations (e.g., corporate funding situations versus
federal ones); this includes collecting data on how scientists, technologists, and policymakers read and evaluate proposals for research funding.
As well, I believe that taking a perspective towards scientists and engineers as
storytelling rhetors, we emphasize the similarities between what we do in the humanities
and social sciences and what they do in the “hard” sciences and engineering; essentially,
we both apply methodological tools to “data”—whether those data are texts, talk, or
enzymes—and attempt to extrapolate theory that accounts for other texts, talk, or
enzymes. We have both experienced disciplinary controversies and tensions (whether in
the form of moving from Newtonian to Einsteinian physics or moving from structuralist to
post-structuralist theories of reading and writing) and we both recognize the contingency of
our knowledge claims.
Indeed, discussions of the constructivist and, therefore, contingent nature of
knowledge claims has gained the attention of researchers studying how to improve current
science teaching (e.g., Duit, 1991; Glynn, 1991; Glynn, Yeany, & Britton, 1991). Martin and
Miller (1988), in fact, recommend that scientific stories act as one source of information to
introduce students to the complexities of scientific thinking. Criticizing contemporary
science texts, they write
175
The science books adopted in most schools transmit a body of knowledge
with little attention to the bodies for whom that knowledge is intended.
. . . These texts offer children no stories, no connections between forms and
forces, between observers and observed. Without this profound
connectivity which is the lifeblood of science, the body of scientific
knowledge can be reduced to a corpse. Through a storytelling mode,
scientific knowledge can be kept alive for children (259).
And Martin and Brouwer (1991), as well, urge that “an authentic portrayal of science would
be one that included, where appropriate, a development of the methodological,
epistemological, personal, private, public, historical, societal, and technological aspects
of science as well as addressing the question of the aims or purposes implicit within
science” (708).
My argument, therefore, is that extending our collection of case studies from
different disciplines has the potential to help us create a database of issues, concerns,
values, discourse cues, and so on. This database, in turn, should situate our teaching of
technical communication for the sciences and engineering, and result in a collection of
detailed descriptions of actual writing projects as they evolve over time. Technical
students are often skeptical about the importance of writing to their particular disciplines,
and this represents a useful way of letting them know that we, too, have collected and
analyzed our data. Our students need to learn that, as Raymond puts it, simply “presenting
the facts” is the “least interesting” aspect of most writing in the sciences and engineering.
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Appendix A—Schriver’s Agenda of Research Questions
• What are the relationships among cognitive, social, and cultural factors in document
design?
• Are there differences between writers and readers across cultures? Do the same writing
strategies, for example, work for Japanese- and English-speaking audiences? Do readers
in various cultures read and access information in similar ways?
• What is the relation between oral and written communication in social contexts? For
example, how do oral and written language work together in educational, government, or
corporate contexts? Are there culture-specific patterns?
• What is the role of writers’ knowledge in document design? Subject-matter knowledge?
Linguistic knowledge? Perceptual knowledge? Strategic knowledge? Rhetorical
knowledge?
• What constitutes skill in document design? What do document designers need to know to
become expert? What experiences do they need?
• What is the best means for soliciting subject-matter knowledge from experts? How
should writers without subject-matter expertise proceed?
• How can research on reading best be applied to document design?
• What are the principles underlying the visual design of effective text? Do some visual
information structures meet readers’ needs better than others?
• What are the best strategies for designing texts that serve multiple functions, for
example, to inform and persuade?
• How does collaboration with other experts shape the nature of the document design
process? What are the optimal collaboration points among people (e.g., writers,
designers, and subject-matter experts) contributing to the same text?
• How can technology facilitate the document design process? What constraints does
technology place on the document design process? What are the key features of a user
interface that would best support collaborative document design?
• How do the needs of expert audiences differ from those of lay audiences? How can the
needs of multiple audiences best be addressed?
177
Appendix A—Schriver’s Agenda, Continued
• Which text-evaluation methods are best suited for judging text quality? At what
point(s) in the document design process are particular text-evaluation methods most
useful; e.g., what tests should be used for first drafts? Can we develop more sensitive
text-evaluation methods than are currently available? Are there effective combinations
of existing methods?
• What do writers learn from testing documents and observing readers interacting with
text? Are there long-term benefits? Can we consolidate this learning and teach it more
directly?
• What are the most likely candidate text features for building online text critiquers? Can
the computer help us in text evaluation more than it has? (325).
178
Appendix B—Instructions for Taping a Protocol
A protocol is a technique whereby a writer orally records his/her thinking about a
document while writing it. You will be producing your “thinking aloud” protocol simply by
turning on your tape recorder and verbalizing your thoughts about the document. The most
important thing about this protocol is that you say everything out loud as you are thinking
and writing your message. (We realize, of course, that it’s impossible to say absolutely
everything you’re thinking while you’re writing, so just try to say as much as you can.) Be
assured that there are no incorrect or correct comments; stray remarks and seemingly
irrelevant comments are fine. The length of your commentary should be about thirty to
forty minutes. Because we would like your commentary to be as spontaneous as possible
under the circumstances, it’s especially important that you not “rehearse” your commentary
before recording it. If you are interrupted, simply note the interruption and its length when
you restart the tape (adapted from Blyler, 1989, 65-66).
179
Appendix C—Questions Asked of Fifteen Academic Researchers
•
From whom do you seek research funding?
•
How does dealing with industry differ from government funding agencies?
•
What would motivate you to choose one funding agency over another?
•
How do you usually communicate with funding agencies?
•
When did you start working with funding agencies?
•
What do you think funding agencies hope to gain from your research?
•
How do you think your research will be used by funding agencies?
•
How could funding agencies improve their relationship with you?
•
What would you change about working with funding agencies?
•
How do you think future academic-funding agency relationships will evolve?
180
Appendix D—The Episodes and the Multiple Data Types
Total #
Total #
Episodes
% of Total
Words
Max #
Words/
Episode
Min #
Words/
Episode
Mean #
Words/
Episode
OpenEnded Ints.
4
35
54.6%
482
58
270
DiscsBased Ints.
3
5
16%
214
55
134.5
Protocs.
2
11
73.2%
194
67
130.5
Taped
Sessions
2
20
24.3%
246
60
153
Tot/Ave
11
71
42%
284
60
172
Table: Breakdown and percentages of the 71 episodes analyzed across the multiple data
types.
181
Appendix E—Questions Asked of the Biochemical Engineer
•
What is the chronology of your research, journal writing and proposal writing?
•
What is the relationship between your instrumentation and theory?
•
Does the relationship between your instrumentation and your journal writing differ
from the relationship between your instrumentation and your proposal writing?
•
When did you begin writing your proposal based on research you had carried out in
the laboratory and written about for a journal audience?
•
What is the chronology of your proposal writing?
•
What are your future research/funding plans based on this research?
•
How has your research team evolved over the journal writing and proposal writing
chronology?
•
What were your reasons for collaborating on your proposal?
•
Do you perceive any differences between planning your collaborative project and
planning the written proposal?
•
How did you collaboratively agree on the organization of the proposal?
•
What, if any, problems, difficulties, or tensions did you encounter in creating the
proposal collaboratively?
182
Appendix F—Chronology of Raymond’s Writing Projects
Time
Research activity or writing effort
1984-1987:
Original laboratory work (focus on calorimetry technique
and the unfolding of enzymes).
May, 1988:
First draft of research article submitted to biotechnology
journal.
July, 1988:
Research article returned with reviewer comments (new
focus: concentration effect and purity issue).
September, 1988:
More laboratory work and revision (armed with
data/answers; now attempting to resolve domain versus
heterogeneity conflict).
End of May, 1989:
Research article completed and re-submitted to
biotechnology journal.
September, 1989:
Begins working on initial proposal-writing effort.
December, 1989:
Research article published in biotechnology journal.
March, 1990:
First discussions between Raymond and Larry about the
possibility of doing a collaborative proposal for NIH.
July, 1990:
Raymond writes a short five-page outline of the proposal.
September 4, 1990:
Raymond and Larry receive an RFP from the NIH
informing them that a special session of particular
relevance to their research is being held on October 1, 1990.
September 10, 1990:
Raymond writes first draft of the proposal (based on his
July draft).
September 21, 1990:
Raymond and Larry’s first meeting.
September 26, 1990:
Raymond and Larry’s second meeting.
October 1, 1990:
Proposal submitted to NIH.
183
Appendix G—Results of the Data Analysis
Planning
Open-ended
16%
Writing/
Evaluat-
Total %
Revising
ing
1%
32%
49%
6%
7%
interviews
Discourse-based
1%
interviews
Protocols
16%
Taped meetings
28%
Total %
45%
16%
28%
17%
38%
100%
Table 1: Overview of the various data sources and their relation to planning, revising, and
evaluation.
For the purposes of simplicity, in the tables that follow, I have abbreviated each
of the six categories as follows: “Char. Aud. (1)” are episodes where the biochemical
engineers characterized their audience; “Ant. Aud. (2)” are episodes where they
anticipated audience reactions; “Alt. Res. (3)” are episodes where they altered existing
research plans; “Int. Sci. Res. (4)” are episodes where they integrated existing scientific
research into their texts; “Ident. Tech. (5)” are episodes where they identified technical
issues and constraints; and, “Rhet. Alts. (6)” are episodes where they discussed rhetorical
alternatives or strategies for writing. In the tables that follow, these abbreviations will
be further shortened to “P” (for Planning), “R” (for Writing/Revising), and “E” (for
evaluating) followed by the numbers one through six (e.g., “E3” indicates that, while
“Evaluating” their texts, the biochemical engineers decided to alter their existing
research plans).
184
Int. Sci.
Res.
(4)
Disc.
Tech. (5)
Rhet.
Alts.
(6)
Total
4%
3%
1.5%
7%
19.5%
6%
1.5%
28%
35.5%
1.5%
8%
16.5%
Int. Sci.
Res.
(4)
10%
10%
Disc.
Tech. (5)
3%
3%
Rhet.
Alts.
(6)
15.5%
15.5%
71.5%
100%
Char.
Aud. (1)
Char.
Aud. (1)
Ant. Aud.
(2)
4%
Ant. Aud.
(2)
Alt. Res.
(3)
Total
Alt. Res.
(3)
7%
4%
10%
7%
6%
1.5%
Table 2: Percentage breakdown of all three writing projects (i.e., the journal-writing
project, the individual proposal-writing effort, and the collaborative proposal-writing
project) and the various activities carried out by the biochemical engineer and his
colleague.
185
P1
P1
P2
3%
(6.5%)
P2
P4
P5
P6
Total
3%
1.5%
1.5%
4%
12.5%
(6.5%)
(3%)
(3%)
(9%)
(28%)
1.5%
13%
14%
(3%)
(28%)
(31%)
P3
P3
1.5%
1.5%
6%
9%
(3%)
(3%)
(13%)
(19%)
3%
3%
(6.5%)
(6.5%)
3%
3%
(6.5%)
(6.5%)
4%
4%
(9%)
(9%)
P4
P5
P6
Total
3%
4.5%
1.5%
3%
1.5%
33%
46%
(6.5%)
(9.5%)
(3%)
(6%)
(3%)
(72%)
(100%)
Table 3: Percentage breakdown of the activities that the biochemical engineers
emphasized during the planning phase of all three writing projects. P1 is “Characterizing
the audience,” P2 is “Anticipating audience reaction to the document,” P3 is “Altering
existing research plans,” P4 is “Integrating existing scientific research or research
literature,” P5 is “Discussing technical issues,” and P6 is “Discussing rhetorical
alternatives.”
186
R1
R1
R2
R3
R4
R5
R6
Total
1.5%
1.5%
(9%)
(9%)
R2
3%
3%
(17.5%)
(17.5%)
1.5%
1.5%
(9%)
(9%)
4%
4%
(23.5%)
(23.5%)
7%
7%
(41%)
(41%)
1.5%
15.5%
17%
(9%)
(91%)
(100%)
R3
R4
R5
R6
Total
Table 4: Percentage breakdown of the activities that the biochemical engineers
emphasized during the writing/revising phase of all three writing projects. R1 is
“Characterizing the audience,” R2 is “Anticipating audience reaction to the document,” R3
is “Altering existing research plans,” R4 is “Integrating existing scientific research or
research literature,” R5 is “Discussing technical issues,” and R6 is “Discussing rhetorical
alternatives.”
187
E1
E1
E2
1%
(3%)
E2
E3
E4
E5
E6
Total
1%
3%
5%
(3%)
(8%)
(14%)
4%
1%
13%
18%
(10.5%)
(3%)
(35%)
(48.5%)
6%
1%
7%
(16%)
(3%)
(19%)
3%
3%
(8%)
(8%)
4%
4%
(10.5%)
(10.5%)
E3
E4
E5
E6
Total
1%
5%
6%
1%
24%
37%
(3%)
(13.5%)
(16%)
(3%)
(64.5%)
(100%)
Table 5: Percentage breakdown of the activities that the biochemical engineers
emphasized during the evaluation phase of all three writing projects. E1 is
“Characterizing the audience,” E2 is “Anticipating audience reaction to the document,” E3
is “Altering existing research plans,” E4 is “Integrating existing scientific research or
research literature,” E5 is “Discussing technical issues,” and E6 is “Discussing rhetorical
alternatives.”
188
Disc.
Tech. (5)
Rhet.
Alts.
(6)
Total
3%
10%
22%
15%
27%
12%
27%
Int. Sci.
Res.
(4)
3%
3%
Disc.
Tech. (5)
6%
6%
Rhet.
Alts.
(6)
15%
15%
61%
100%
Char.
Aud. (1)
Char.
Aud.
(1)
Ant. Aud.
(2)
6%
3%
Ant. Aud.
(2)
Int. Sci.
Res.
(4)
12%
Alt. Res.
(3)
Total
Alt. Res.
(3)
12%
6%
15%
12%
3%
3%
3%
Table 6: Percentage breakdown of the collaborative proposal-writing project and the
various activities carried out by the biochemical engineer and his colleague.
189
P5
P6
Total
4%
8.5%
20.5%
21%
29.5%
17%
25%
P4
4%
4%
P5
8.5%
8.5%
P6
12.5%
12.5%
71.5%
100%
P1
P1
P2
4%
4%
P2
P4
8.5%
P3
Total
P3
4%
4%
12.5%
4%
4%
4%
4%
Table 7: Percentage breakdown of the activities that the biochemical engineers
emphasized during the planning phase of the collaborative proposal-writing project. P1 is
“Characterizing the audience,” P2 is “Anticipating audience reaction to the document,” P3
is “Altering existing research plans,” P4 is “Integrating existing scientific research or
research literature,” P5 is “Discussing technical issues,” and P6 is “Discussing rhetorical
alternatives.”
190
E1
E1
E2
E3
11%
E2
E4
E5
E6
Total
11%
22%
22%
E3
22%
33%
33%
E4
E5
E6
Total
11%
22%
33%
22%
22%
33%
~100%
Table 8: Percentage breakdown of the activities that the biochemical engineers
emphasized during the evaluation phase of the collaborative proposal-writing project. E1
is “Characterizing the audience,” E2 is “Anticipating audience reaction to the document,”
E3 is “Altering existing research plans,” E4 is “Integrating existing scientific research or
research literature,” E5 is “Discussing technical issues,” and E6 is “Discussing rhetorical
alternatives.”
191
Char.
Aud.
(1)
Rhet.
Alts.
(6)
Total
Char.
Aud. (1)
6.5%
6.5%
Ant. Aud.
(2)
27%
27%
6.5%
13%
20%
20%
33.5%
33.5%
93.5
100%
Alt. Res.
(3)
Ant. Aud.
(2)
Alt. Res.
(3)
6.5%
Int. Sci.
Res.
(4)
Int. Sci.
Res.
(4)
Disc.
Tech. (5)
Disc.
Tech. (5)
Rhet.
Alts.
(6)
Total
6.5%
Table 9: Percentage breakdown of the initial proposal-writing project and the various
activities carried out by the biochemical engineer.
192
R1
R2
R3
R4
R5
R6
Total
R2
18%
18%
R3
9%
9%
R4
27%
27%
R6
46%
46%
Total
100%
100%
R1
R5
Table 10: Percentage breakdown of the activities that the biochemical engineer
emphasized during the writing/revising phase of the initial proposal-writing project. R1
is “Characterizing the audience,” R2 is “Anticipating audience reaction to the document,”
R3 is “Altering existing research plans,” R4 is “Integrating existing scientific research or
research literature,” R5 is “Discussing technical issues,” and R6 is “Discussing rhetorical
alternatives.”
193
Char.
Aud. (1)
Char.
Aud.
(1)
Ant. Aud.
(2)
4.5%
4.5%
9%
4.5%
4.5%
Ant. Aud.
(2)
Alt. Res.
(3)
Int. Sci.
Res.
(4)
Disc.
Tech. (5)
Rhet.
Alts.
(6)
Total
18%
51%
60%
Alt. Res.
(3)
4.5%
4.5%
Int. Sci.
Res.
(4)
13%
13%
4.5%
4.5%
73%
100%
Disc.
Tech. (5)
Rhet.
Alts.
(6)
Total
4.5%
9%
13.5%
Table 11: Percentage breakdown of Raymond’s journal-article project and the various
activities he carried out.
194
P1
P1
14%
P2
P3
P4
P5
P6
14%
P2
Total
28%
58%
58%
14%
14%
72%
100%
P3
P4
P5
P6
Total
14%
14%
Table 12: Percentage breakdown of the activities that the biochemical engineer
emphasized during the planning phase of the journal-article project. P1 is “Characterizing
the audience,” P2 is “Anticipating audience reaction to the document,” P3 is “Altering
existing research plans,” P4 is “Integrating existing scientific research or research
literature,” P5 is “Discussing technical issues,” and P6 is “Discussing rhetorical
alternatives.”
195
E1
E2
E1
7%
E2
7%
E3
E4
E5
E6
Total
7%
7%
50%
64%
E3
7%
7%
E4
14%
14%
7%
7%
78%
~100%
E5
E6
Total
14%
7%
Table 13: Percentage breakdown of the activities that the biochemical engineer
emphasized during the evaluation phase of the journal-article project. E1 is
“Characterizing the audience,” E2 is “Anticipating audience reaction to the document,” E3
is “Altering existing research plans,” E4 is “Integrating existing scientific research or
research literature,” E5 is “Discussing technical issues,” and E6 is “Discussing rhetorical
alternatives.”
196
1
2
3
4
5
6
7
8
9
10
11
12
13
14
WL
1.8
1.6
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
SL
20
20
25
23
22
23
22
25
25
19
19
19
19
19
PL
4
5
6
6
6
6
6
17
18
7
7
5
5
5
#S
234
117
104
114
300
299
364
459
481
755
759
748
744
775
PV
27
23
27
25
36
36
35
37
36
29
29
30
30
29
#PP
3.3
2.6
3.2
3.0
3.3
3.3
3.2
3.5
3.5
2.6
2.5
2.6
2.6
2.5
Table 14: The syntactical evolution of the 14 proposal drafts over the three-week writing
period: WL is the average word length in syllables; SL is the average sentence length in
words; PL is the average paragraph length in sentences; #S is the number of sentences in
each draft; PV is the percentage of passive voice constructions in each draft, and; #PP is
the number of prepositions per sentence.
197
1
2
3
4
5
6
7
8
9
10
11
12
13
14
(1)
15
12
12
12
11
11
10
9
8
7
7
7
7
7
(2)
25
4
4
4
19
19
15
22
22
20
21
21
22
20
(3)
8
84
76
74
50
50
40
32
33
24
24
22
21
22
8
8
7
6
6
6
7
6
27
29
30
27
27
28
28
30
(6)
5
5
5
6
6
(7)
10
10
11
9
9
(4)
(5)
32
20
20
Table 15: The development and percentage breakdown of each section of the 14 proposal
drafts over the three-week writing period: (1) is the Specific Aims section; (2) is the
Significance section; (3) is the Preliminary Efforts section, (4) is the Proposed Research:
Materials and Methods section; (5) is the Research Plan section; (6) is References section,
and; (7) is the Appendix: Expanded Methods and Prior Work section.
198
Section of
Proposal
Specific
Aims
Signific.
Methods
Research
Plan
Tables
Figures
Refs.
Technical
Expertise
CD
DSC
Gene
Fusion
Tail
Selection
Metal
Binding
pH/tm.
Site-dir.
Mut.
IMAC
Model
Choice
Admin.
Details
Factfinding
Farming
work out
Total Tasks
Meeting
Raymond’s
Task Plan
(6)
One
Larry’s
Task Plan
(2)
1
Meeting
Raymond’s
Task Plan
(4)
Two
Larry’s
Task Plan
(6)
(18)
2
2
1
1
1
3
1
2
2
2
3
2
1
(4)
2
3
3
(17)
1
1
4
1
1
1
(4)
1
1
(5)
2
1
2
(4)
1
1
1
1
1
2
1
1
2
1
2
1
1
1
2
3
(5)
(3)
(8)
3
3
6
2
15
2
7
11
10
43
Table 16: The distribution of planned tasks established during the two taped meetings
between the biochemical engineers.
199
Appendix H—Chronology of the 14 Proposal Drafts
Number
Day
Date
# of Words
Version 1:
Monday
September 10th
5313
Words
Version 2:
Tuesday
September 11th
2440
Words
Version 3:
Thursday
September 13th
2624
Words
Version 4:
Monday
September 17th
2721
Words
Version 5:
Tuesday
September 18th
7018
Words
Version 6:
Wednesday
September 19th
7164
Words
Version 7:
Thursday
September 20th
8585
Words
Meeting 1:
Friday
September 21st
Version 8:
Wednesday
September 26th
11771
Words
Meeting 2:
Wednesday
September 26th
Version 9:
Thursday
September 27th
12308
Words
Version 10:
Friday
September 28th
14832
Words
Version 11:
Saturday
September 29th
14898
Words
Version 12:
Saturday
September 29th
14814
Words
Version 13:
Sunday
September 30th
14837
Words
Version 14:
Monday
October 1st
15272
Words
200
Appendix I—Evolution of the NIH Proposal’s Specific Aims Section
The First Draft—Monday, September 10th Version
1.
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
2.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
3.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
4.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
DSC to ensure the engineered protein is not conformationally heterogeneous and to
characterize any alteration of conformation, or variation in crosslinking pattern,
that may of occurred. (Is this protein crosslinked? If so we might want to look at
reduced and oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe answer
this question.)
5.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein (need to look
at finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine, for example, if the presence of the added fragment can suppress
the effects the metal ions have on the enzyme’s endotherm due to the fragment
being able to bind the metal ion preferentially.
7.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added are present in reduced form. Additionally, determine if in the presence of
metal ion, the kinetics of the probe reaction is altered which could be an indication
of reduced accessibility of the probe for cysteine due to secondary structure
formation.
8.
perform uv and near visible light spectroscopy experiments employing the binding
of Co(II) as a probe a Me(II)-S coordination occurring.
201
Changes to the First Draft—Tuesday, September 11th Version
1
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
2.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
3.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
4. 1.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
DSC to ensure the engineered protein is not conformationally heterogeneous and to
characterize any alteration of conformation, or variation in crosslinking pattern,
that may of occurred. (Is this protein crosslinked? If so we might want to look at
reduced and oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe answer
this question.)
5. 2.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein (need to look
at finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
6. 3.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine, for example, if the presence of the added fragment can suppress
the effects the metal ions have on the enzyme’s endotherm due to the fragment
being able to bind the metal ion preferentially.
7. 4.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added cysteines are present in reduced form. Additionally, determine if in the
presence of metal ion, the kinetics of the probe reaction is altered which could be
an indication of reduced accessibility of the probe for cysteine due to secondary
structure formation.
8. 5.
perform Perfrom uv and near visible light spectroscopy experiments employing the
binding of Co(II) as a probe a Me(II)-S coordination occurring.
202
Changes to the Second Draft—Thursday, September 13th Version
1.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
DSC to ensure the engineered protein is not conformationally heterogeneous and to
characterize any alteration of conformation, or variation in crosslinking pattern,
that may of occurred. (Is this protein crosslinked? If so we might want to look at
reduced and oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe answer
this question.)
2.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein (need to look
at finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
3.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine, for example, if the presence of the added metal-binding,
terminal fragment can suppress the effects the metal ions have on the enzyme’s
endotherm due to the fragment being able to preferentially bind the metal ion
preferentially.
4.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added cysteines are present in reduced form. Additionally, determine if in the
presence of metal ion, the kinetics of the probe reaction is altered which could be
an indication of reduced accessibility of the probe for cysteine due to secondary
structure formation and metal ion coordination .
5.
Perfrom uv and near visible light spectroscopy experiments employing the binding
of Co(II) as a probe a of Me(II)-S coordination occurring.
203
Changes to the Third Draft—Monday, September 17th Version
1.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference different amounts of background histidine have been removed) to wild
type with DSC to ensure the engineered protein is not conformationally
heterogeneous and to characterize any alteration of conformation, or variation in
crosslinking pattern, that may of occurred. (Is this protein crosslinked? If so we
might want to look at reduced and oxidized forms to see if a variation in
crosslinking pattern may have occurred due to the substitutions. A look at the
structure could also maybe answer this question.)
2.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein (need to look
at finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
3.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine if the presence of the metal-binding, terminal fragment can
suppress the effects the metal ions have on the enzyme’s endotherm due to the
fragment being able to preferentially bind the metal ion.
4.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added cysteines are present in reduced form. Additionally, determine if in the
presence of metal ion, the kinetics of the probe reaction is altered which could be
an indication of reduced accessibility of the probe for cysteine due to secondary
structure formation and metal ion coordination.
5.
Perfrom Perform uv and near visible light spectroscopy experiments employing the
binding of Co(II) as a probe of Me(II)-S coordination occurring.
204
Changes to the Fourth Draft—Tuesday, September 18th Version
1.
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
2.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
3.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
1. 4.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but different
difference amounts of background histidine have been removed) to wild type with
DSC to ensure the engineered protein is not conformationally heterogeneous and to
characterize any alteration of conformation, or variation in crosslinking pattern,
that may of occurred. (Is this protein crosslinked? If so we might want to look at
reduced and oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe answer
this question.)
2. 5.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein (need to look
at finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
3. 6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine, for example, if the presence of the added metal-binding,
terminal fragment can suppress the effects the metal ions have on the enzyme’s
endotherm due to the fragment being able to preferentially bind the metal ion
preferentially .
4. 7.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added cysteines are present in reduced form. Additionally, determine if in the
presence of metal ion, the kinetics of the probe reaction is altered which could be
an indication of reduced accessibility of the probe for cysteine due to secondary
structure formation and metal ion coordination.
5. 8.
Perform perform uv and near visible light spectroscopy experiments employing the
binding of Co(II) as a probe of a Me(II)-S coordination occurring.
205
Changes to the Fifth Draft—Wednesday, September 19th Version
1.
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
2.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
3.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
4.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
DSC to ensure the engineered protein is not conformationally heterogeneous and to
characterize any alteration of conformation, or variation in crosslinking pattern,
that may of occurred. (Is this protein crosslinked? If so we might want to look at
reduced and oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe answer
this question.)
5.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein (need to look
at finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine, for example, if the presence of the added fragment can suppress
the effects the metal ions have on the enzyme’s endotherm due to the fragment
being able to bind the metal ion preferentially.
7.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added are present in reduced form. Additionally, determine if in the presence of
metal ion, the kinetics of the probe reaction is altered which could be an indication
of reduced accessibility of the probe for cysteine due to secondary structure
formation.
8.
perform uv and near visible light spectroscopy experiments employing the binding
of Co(II) as a probe a Me(II)-S coordination occurring.
206
Changes to the Sixth Draft—Thursday, September 20th Version
1.
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
2.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
3.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
4.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
DSC to ensure the engineered protein is not conformationally heterogeneous and to
characterize any alteration of conformation, or variation in crosslinking pattern,
that may of occurred. (Is this protein crosslinked? If so we might want to look at
reduced and oxidized forms to see if a variation in crosslinking pattern may have
occurred due to the substitutions. A look at the structure could also maybe answer
this question.)
5.
Characterize the transition of the terminal peptide in the presence and absence of
metal ion to confirm whether finger structure formation can occur in the presence of
metal ion and what the enthalpy change is compared to the protein(need to look at
finger literature to see what has been done on this topic or eliminate if you think
these experiments are not really feasible).
6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC. Determine, for example, if the presence of the added fragment can suppress
the effects the metal ions have on the enzyme’s endotherm due to the fragment
being able to bind the metal ion preferentially.
7.
Perform sulfhydryl group titrations with DTNB and 4-PDS to ensure that all the
added are present in reduced form. Additionally, determine if in the presence of
metal ion, the kinetics of the probe reaction is altered which could be an indication
of reduced accessibility of the probe for cysteine due to secondary structure
formation.
8.
perform uv and near visible light spectroscopy experiments employing the binding
of Co(II) as a probe a Me(II)-S coordination occurring.
207
Changes to the Seventh Draft—Wednesday, September 26th Version
1.
To construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. This model proteins will allow a
systematic characterization of IMAC for protein purification and as an analytical
technique for identification and characterization of metalloproteins.
1. 2.
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
2. 3.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
3. 4.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
4. 5.
Contrast engineered ß-lactamases ß -lactamases (i.e. contain same terminal
sequence but difference amounts of background histidine have been removed) to
wild type with DSC Differential Scanning Calorimetry (DSC) to ensure the
engineered protein is not conformationally heterogeneous and to characterize any
alteration of conformation, or variation in crosslinking pattern, that may of
occurred.
6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC , IMAC, CD spectroscopy, and binding studies. Determine, for example, if the
presence of the added fragment can suppress the effects the metal ions have on the
enzyme’s endotherm due to the fragment being able to bind the metal ion
preferentially.
208
Changes to the Eighth Draft—Thursday, September 27th Version
1.
To construct and produce a family of ß ß- lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. This model proteins will allow a
systematic characterization of IMAC for protein purification and as an analytical
technique for identification and characterization of metalloproteins.
2.
To demonstrate that the portion of elution profile which are without any
contaminant proteins could be utilized for one step purification of target protein
from a cell extract by directing the elution of a target protein towards those area
employing gene fusion techniques.
3.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
4.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
5.
Contrast engineered ß ß- lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
Differential Scanning Calorimetry (DSC) to ensure the engineered protein is not
conformationally heterogeneous and to characterize any alteration of
conformation, or variation in crosslinking pattern, that may of occurred. occurr.
6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC, IMAC, CD spectroscopy, and binding studies. Determine, for example, if the
presence of the added fragment can suppress the effects the metal ions have on the
enzyme’s endotherm due to the fragment being able to bind the metal ion
preferentially.
209
Changes to the Ninth Draft—Friday, September 28th Version
1.
To construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. This model proteins will allow a
systematic characterization of IMAC for protein purification and as an analytical
technique for identification and characterization of metalloproteins.
2.
To demonstrate that the portion of elution profile which are without any
contaminant contaminating proteins could be utilized for one step purification of
target protein from a cell extract by directing the elution of a target protein
towards those area employing through the application of gene fusion techniques.
3.
To assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
4.
To examine a possible role for IMAC as a simple and rapid tool for identification of
zinc and other metal binding proteins in different preparations.
5.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
Differential Scanning Calorimetry (DSC) to ensure the engineered protein is not
conformationally heterogeneous and to characterize any alteration of
conformation, or variation in crosslinking pattern, that may occurr. occur.
6.
Contrast metal binding behavior of engineered proteins and native protein with
DSC, IMAC, CD spectroscopy, and binding studies. Determine, for example, if the
presence of the added fragment can suppress the effects the metal ions have on the
enzyme’s endotherm due to the fragment being able to bind the metal ion
preferentially.
210
Changes to the Tenth Draft—Saturday, September 29th First Version
1.
To Construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. This These model proteins will
allow for a systematic characterization of IMAC for protein purification and as an
analytical technique for the identification and characterization of
metalloproteins.
2.
Determine how sample pretreatment (e.g. remove bound metal ions first) may alter
the elution profile of host cell proteins so that further information on the relative
abundance of zinc binding and nonbinding proteins is obtained. Also ascertain
whether alternative “window” opportunites exist via different pretreatments.
2. 3.
To Demonstrate that the portion portions of elution profile which are without any
that are deviod of contaminating proteins could be utilized for an one-step
purification of a target protein from a cell extract by directing the elution of a
target protein towards those area portions through the application of gene fusion
techniques.
3. 4.
To Assess whether a protein demonstrating multiple binding site for a metal ion
will utilize one site preferentially or multiple attachment will occur; and examine
the implications of these results for protein purification strategies when
employing metal binding affinity peptides.
5.
Contrast engineered ß-lactamases (i.e. contain same terminal sequence but
difference amounts of background histidine have been removed) to wild type with
Differential Scanning Calorimetry (DSC) to ensure the engineered protein is not
conformationally heterogeneous and to characterize any alteration of
conformation, or variation in crosslinking pattern, that may occur.
6. 5.
Contrast Characterize the model proteins and then contrast the metal binding
behavior of engineered proteins and native protein with DSC, IMAC, light
spectroscopy, CD spectroscopy, and metal binding studies. Determine, for example,
if the presence of the added fragment a tail can suppress the effects the metal ions
have on the effect metal ion binding has on an enzyme’s endotherm due to the
fragment tail being able to bind the metal ion preferentially. Then relate this
molecular-level information to the IMAC results.
211
Changes to the Eleventh Draft—Saturday, Sept. 29th Second Version
1.
Construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. These model proteins will allow
for a systematic characterization of IMAC for protein purification and as an
analytical technique for the identification and characterization of
metalloproteins.
2.
Determine how sample pretreatment (e.g. remove bound metal ions first) may alter
the elution profile of host cell proteins so that further information on the relative
abundance of zinc binding and nonbinding proteins is obtained. Also ascertain
whether alternative “window” opportunites exist via different pretreatments.
3.
Demonstrate that the portions of elution profile that are deviod of contaminating
proteins could be utilized for an one-step purification of a target protein from a cell
extract by directing the elution of a target protein towards those portions through
the application of gene fusion techniques.
4.
Assess whether a protein demonstrating multiple binding site for a metal ion will
utilize one site preferentially or multiple attachment will occur; and examine the
implications of these results for protein purification strategies when employing
metal binding affinity peptides.
5.
Characterize the model proteins and then contrast the metal binding behavior of
engineered proteins and native protein with DSC, light spectroscopy, CD
spectroscopy, and metal binding studies. Determine, for example, if the presence of
a tail can suppress the effect metal ion binding has on an enzyme’s endotherm due
to the tail being able to bind the metal ion preferentially. Then relate this
molecular-level information to the IMAC results.
6.
Apart from the aim of using IMAC as a one-step protein isolation procedure,
examine the results from the standpoint of using IMAC as a simple and rapid tool
for identifying zinc and other metal binding proteins in different preparations.
212
Changes to the Twelfth Draft—Sunday, September 30th Version
1.
Construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. These model proteins will allow
for a systematic characterization of IMAC for protein purification and as an
analytical technique for the identification and characterization of
metalloproteins.
2.
Determine how sample pretreatment (e.g. remove bound metal ions first) may alter
the elution profile of host cell proteins so that further information on the relative
abundance of zinc binding and nonbinding proteins is obtained. Also ascertain
whether alternative “window” opportunites exist via different pretreatments.
3.
Demonstrate that the portions of elution profile that are deviod devoid of
contaminating proteins could be utilized for an one-step purification of a target
protein from a cell extract by directing the elution of a target protein towards those
portions through the application of gene fusion techniques.
4.
Assess whether a protein demonstrating multiple binding site for a metal ion will
utilize one site preferentially or multiple attachment will occur; and examine the
implications of these results for protein purification strategies when employing
metal binding affinity peptides.
5.
Characterize the model proteins and then contrast the metal binding behavior of
engineered proteins and native protein with DSC, light spectroscopy, CD
spectroscopy, and metal binding studies. Determine, for example, if the presence of
a tail can suppress the effect metal ion binding has on an enzyme’s endotherm due
to the tail being able to bind the metal ion preferentially. Then relate this
molecular-level information to the IMAC results.
6.
Apart from the aim of using IMAC as a one-step protein isolation procedure,
examine the results from the standpoint of using IMAC as a simple and rapid tool
for identifying zinc and other metal binding proteins in different preparations.
213
Changes to the Thirteenth & Final Draft—Monday, October 1st Version
1.
Construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. These model proteins will allow
for a systematic characterization of IMAC for protein purification and as an
analytical technique for the identification and characterization of
metalloproteins.
2.
Determine how sample pretreatment (e.g. remove bound metal ions first) may alter
the elution profile of host cell proteins so that further information on the relative
abundance of zinc binding and nonbinding proteins is obtained. Also ascertain
whether alternative “window” opportunities exist via can be generated by using
different pretreatments.
3.
Demonstrate that the portions of elution profile that are devoid of contaminating
proteins could be utilized for an one-step purification of a target protein from a cell
extract by directing the elution of a target protein towards those portions through
the application of gene fusion techniques.
4.
Assess whether a protein demonstrating multiple binding site for a metal ion will
utilize one site preferentially or multiple attachment will occur; and examine the
implications of these results for protein purification strategies when employing
metal binding affinity peptides.
5.
Characterize the model proteins and then contrast the metal binding behavior of
engineered proteins and native protein with DSC, light spectroscopy, CD
spectroscopy, and metal binding studies. Determine, for example, if the presence of
a tail can suppress the effect metal ion binding has on an enzyme’s endotherm due
to the tail being able to bind the metal ion preferentially. Then relate this
molecular-level information to the IMAC results.
6.
Apart from the aim of using IMAC as a one-step protein isolation procedure,
examine the results from the standpoint of using IMAC as a simple and rapid tool
for identifying zinc and other metal binding proteins in different preparations.
214
The Final Draft—Monday, October 1st Version
1.
Construct and produce a family of ß-lactamases, as model proteins, using site
directed mutagenesis and gene fusion techniques. These model proteins will allow
for a systematic characterization of IMAC for protein purification and as an
analytical technique for the identification and characterization of
metalloproteins.
2.
Determine how sample pretreatment (e.g. remove bound metal ions first) may alter
the elution profile of host cell proteins so that further information on the relative
abundance of zinc binding and nonbinding proteins is obtained. Also ascertain
whether alternative “window” opportunities can be generated by using different
pretreatments.
3.
Demonstrate that the portions of elution profile that are devoid of contaminating
proteins could be utilized for an one-step purification of a target protein from a cell
extract by directing the elution of a target protein towards those portions through
the application of gene fusion techniques.
4.
Assess whether a protein demonstrating multiple binding site for a metal ion will
utilize one site preferentially or multiple attachment will occur; and examine the
implications of these results for protein purification strategies when employing
metal binding affinity peptides.
5.
Characterize the model proteins and then contrast the metal binding behavior of
engineered proteins and native protein with DSC, light spectroscopy, CD
spectroscopy, and metal binding studies. Determine, for example, if the presence of
a tail can suppress the effect metal ion binding has on an enzyme’s endotherm due
to the tail being able to bind the metal ion preferentially. Then relate this
molecular-level information to the IMAC results.
6.
Apart from the aim of using IMAC as a one-step protein isolation procedure,
examine the results from the standpoint of using IMAC as a simple and rapid tool
for identifying zinc and other metal binding proteins in different preparations.
215
Appendix J—Evolution of the Proposal’s Three Major Sections
The Table 1 is organized as follows. II is the percentage of the proposal taken up by
the Significance section over the 14 drafts; a is the IMAC Background and Literature
Survey subsection; b is the DSC Background and Literature Survey subsection, and; c is the
Contributions of the Proposed Research subsection:
II
a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
25
4
4
4
19
19
15
22
22
20
21
21
22
20
(13)
(13)
(10)
(9)
(9)
(8)
(8)
(8)
(8)
(8)
(10)
(10)
(9)
(9)
(9)
(7)
(6)
(3)
(3)
(3)
(4)
(4)
(7)
(6)
b
c
(6)
(6)
(5)
Table 1: The development and percentage breakdown of the Significance section of the
proposal.
Table 2 is organized as follows. III is the percentage of the proposal taken up by
the Preliminary Efforts section over the 14 drafts; a is the Zn(II)-IDA IMAC Experiments
subsection; b is the Cu(II)-IDA IMAC Experiments subsection; c is the Discussion of the
IMAC Results subsection; d is the Overview of Differential Scanning Calorimetry
Experiments subsection; e is the Differential Scanning Calorimetry Results subsection; f is
the Discussion of Differential Calorimetry Results subsection, and; g is the Summary and
Anticipated Utility of Differential Scanning Calorimetry Studies subsection:
216
III
1
2
3
4
5
6
7
8
9
10
11
12
13
14
8
84
76
74
50
50
40
32
33
24
24
22
21
22
(7)
(8)
(6)
(5)
(5)
(5)
(5)
(4)
(4)
(4)
(5)
(4)
(3)
(3)
(2)
(2)
(1)
(1)
(1)
(15)
(9)
(8)
(6)
(7)
(6)
(6)
(6)
(5)
(6)
a
b
c
d
(16)
(8)
(7)
(3)
(3)
(2)
(2)
(2)
(2)
(2)
(2)
(2)
(2)
e
(8)
(7)
(3)
(3)
(2)
(2)
(2)
(2)
(2)
(2)
(2)
(2)
f
(37)
(36)
(3)
(13)
(10)
(8)
(8)
(5)
(5)
(5)
(5)
(5)
g
(23)
(24)
(9)
(9)
(8)
(6)
(6)
(2)
(2)
(2)
(2)
(2)
Table 2: The development and percentage breakdown of the Preliminary Efforts section of
the proposal.
Table 3 is organized as follows. IV is the percentage of the proposal taken up by
the Research Plan section over the 14 drafts; a is the Choice and Construction of Model
Proteins subsection; b is the Characterization of Model Proteins subsection; c is the IMAC
Experiments subsection; d is the Metal Binding Studies subsection, and; e is the
Collaborative Arrangements and Time Table subsection:
1
V
a
b
2
3
4
5
6
7
8
9
10
11
12
13
14
32
20
20
27
29
30
27
27
28
28
30
(32)
(10)
(10)
(8)
(8)
(10)
(9)
(9)
(9)
(9)
(11)
(10)
(10)
(6)
(4)
(4)
(2)
(2)
(2)
(2)
(2)
(4)
(4)
(5)
(4)
(4)
(12)
(12)
(12)
(13)
(12)
c
d
(13)
(17)
(16)
e
Table 3: The development and percentage breakdown of the Research Plan section of the
proposal.
(1)
217
218
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