Ecological Economics 79 (2012) 1–10
Contents lists available at SciVerse ScienceDirect
Ecological Economics
journal homepage: www.elsevier.com/locate/ecolecon
Surveys
Transdisciplinarity: Between mainstreaming and marginalization
Thomas Jahn a, c,⁎, Matthias Bergmann a, b, Florian Keil d
a
Institute for Social–Ecological Research (ISOE), Hamburger Allee 45, 60486 Frankfurt/Main, Germany
Leuphana Universität Lüneburg, Scharnhorststraße 1, 21335 Lüneburg, Germany
c
LOEWE Biodiversity and Climate Research Centre, Senckenberganlage 25, 60325 Frankfurt/Main, Germany
d
keep it balanced, Reichenberger Str. 91, 10999 Berlin, Germany
b
a r t i c l e
i n f o
Article history:
Received 4 July 2011
Received in revised form 13 April 2012
Accepted 22 April 2012
Available online 19 May 2012
Keywords:
Integration
Interdisciplinarity
Problem transformation
Sustainability
Transdisciplinarity
Social–Ecological Research
a b s t r a c t
Transdisciplinarity has a long history of academic discourse. Promoted as an adequate scientific response to
pressing societal problems like climate change, it has recently received common currency in science policy
rhetoric. Nevertheless, despite its increasing popularity, transdisciplinarity is still far from academically
established and current funding practices do not effectively support it at universities and research institutions.
One reason for this deficit is that a universally accepted definition for transdisciplinarity is still not available.
Consequently, quality standards that equally guide researchers, program managers and donors are widely
lacking. Therefore, a rhetorical mainstreaming of transdisciplinarity prevails which risks marginalizing
those who take seriously the integrative efforts creative collaboration requires. The aim of this paper is thus to
find common ground in the transdisciplinarity discourse. Based on an analysis of current scientific literature,
we first identify main features of an emerging shared framework of transdisciplinarity. Second, building upon
this framework, we present a conceptual model of transdisciplinarity that can be used by science and science
policy to characterize different types of transdisciplinarity and their corresponding demands on integration. We
also address the way in which ecological economics could benefit from adopting this model. To conclude, we
propose a general definition of transdisciplinarity.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
In a 2010 correspondence to the journal Nature a group of international scientists warned that Europe's future depends on the funding
of transdisciplinary scientific collaboration (Vasbinder et al., 2010).
They argued that a science that relies on maintaining and reinforcing
disciplinarity will not be able to properly understand the ways in
which our technology impacts the complex, interconnected systems
we depend on. Interventions like this remind us that after years of
debate both within science and science policy, new cultures and practices
of scientific collaboration that cohere with the complex structure of
pressing problems such as climate change or loss of biodiversity have
still not been established. One major reason for this deficit is that transdisciplinarity, at first sight, appears to be a rather elusive concept. In
fact, a universally accepted definition is not available, even after
40 years of intensive scholarly discourse. As a consequence, approved
quality standards that equally guide transdisciplinary researchers,
program managers and donors are widely lacking. It thus comes as no
surprise that appeals for transdisciplinarity often do not spend much
time explaining what they are precisely calling for—a fact that is also
⁎ Corresponding author at: Institute for Social–Ecological Research (ISOE), Hamburger
Allee 45, 60486 Frankfurt/Main, Germany. Tel.: +49 69 707 69 19 0; fax: +49 69 707
69 19 11.
E-mail address: [email protected] (T. Jahn).
0921-8009/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
doi:10.1016/j.ecolecon.2012.04.017
true of other forms of cross-disciplinary collaboration. Yet where concepts or ideas are not properly defined the risk is that a rather shallow
interpretation prevails—a fate that paradigmatically befell the notion
of sustainability. The likely damage that can occur with such a
mainstreaming is that the true challenges of transdisciplinary collaboration are underestimated and that those who take them seriously become
marginalized.
Against this background the article pursues two goals. First, we
aim to identify common ground in the transdisciplinarity discourse.
On the basis of an in-depth analysis of recent academic literature
we present and discuss what can be considered the main features of an
emerging shared framework of transdisciplinarity.1 Second, building
upon this framework, we propose a conceptual model that provides
guidance for framing and classifying transdisciplinary research processes.
Far from being a theory of transdisciplinarity, the model zooms in on
problems of integration and how they can be addressed in research practice. In particular, we suggest how ecological economics could benefit
from the adoption of our model. We developed, applied, and refined
1
We are aware of the number of outstanding studies that summarise the state-ofthe-art in transdisciplinarity (cf. Bergmann and Schramm, 2008; Frodeman et al.,
2010; Hirsch Hadorn et al., 2008; Klein, 2008; Lawrence and Després, 2004; Wickson
et al., 2006). However, we hold that an attempt to synthesize the status of the current
discourse into one shared conceptual framework is still lacking.
2
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
the model over the past years in a joint effort with our colleagues from
the Institute for Social–Ecological Research.
In order to guide the reader through the following sections, a
preliminary definition of transdisciplinarity is already provided here:
Transdisciplinarity is an extension of interdisciplinary forms of the
problem-specific integration of knowledge and methods; while integration refers to scientific questions at the interface of different disciplines
in interdisciplinarity, in transdisciplinarity, on the other hand, it is about
integration at the interface of these scientific questions and societal
problems. In the course of the analysis presented here, we will enrich
this rather technical terminology to finally propose a general definition
of transdisciplinarity that synthesizes our findings. To conclude the
article, we briefly address a couple of controversial topics in the transdisciplinarity discourse and the implications they have for the further
development of a common understanding.
2. An Emerging Shared Framework of Transdisciplinarity
Many authors (cf. Jahn, 2008; Klein, 2004) mark the 1970 OECD
Conference “Interdisciplinarity: Problems of Teaching and Research
in Universities” and the contribution by Erich Jantsch (1970, 1972) as
the birth of the discourse about transdisciplinarity. Although others
(Miller et al., 2008) trace the origins further back to the 1950s by referring to then discussions on the need for cross-disciplinary collaboration
in order to tackle social–ecological issues, it is widely acknowledged
that transdisciplinarity gained its current popularity through the
works of Funtowicz and Ravetz (1990, 1991, 1993) on post-normal
science, and further still through those of Gibbons et al. (1994) on a
new mode of knowledge production (‘Mode 2’). Scholars of ecological
economics referred to transdisciplinarity early on in the development
of their field of research. Costanza and colleagues for example considered transdisciplinarity to be constitutive to ecological economics by
emphasizing that the latter “goes beyond our normal conceptions of
scientific disciplines and tries to integrate and synthesize many different disciplinary perspectives.” (Costanza et al., 1991: 3).
But what is the status of the transdisciplinarity discourse today
after 40 years of intensive scholarly debate? Has it converged to
become a shared conceptual understanding or at least a common
terminology? Or is the discourse still as heterogeneous as a surface
impression of the wealth of literature seems to indicate (cf. Bogner
et al., 2009)? In order to obtain tentative answers to these questions
we closely examined a number of current scientific publications for
their use, conceptualization, and critique of transdisciplinarity. The
literature we studied still covers only a fraction of what has been
published on the subject in recent years. Hence, what we identify in
this section as the main features of an emerging shared framework
of transdisciplinarity strictly applies only to the group of scholars
covered by our sample.
2.1. Transdisciplinarity Starts Off with Complex Societal Problems
Conceiving of transdisciplinarity as problem-oriented research is
not disputed in the current literature (cf. Hirsch Hadorn et al., 2008;
Mobjörk, 2010; Roux et al., 2006; Russell et al., 2008). Historically,
Mode 2 was regarded as operating more generally “within a context
of application in that problems are not set within a disciplinary
framework” (Gibbons et al., 1994: vii); it was then the groundbreaking
2000 conference “Transdisciplinarity: Joint Problem Solving among
Science, Technology and Society” in Zurich (Klein et al., 2001) that clearly
evoked a normative turn in referring to the solution of “real-world
problems” (ibid: 4) such as sustainable development and north–south
relations (ibid: 8) as the epistemic end of transdisciplinary research. A
more direct focus on problems was also suggested earlier on by scholars
of ecological economics as a means to better integrate different disciplinary perspectives (Costanza et al., 1991).
2.2. Transdisciplinarity Involves both Inner-Scientific Cooperation
between Various Disciplines and Fields as well as Cooperation between
Science and Society
Combining “interdisciplinarity” and the “participation” of extrascientific actors seems to be the common recipe for defining transdisciplinarity (Aeberhard and Rist, 2009; Baumgärtner et al., 2008;
Becker, 2002; Hirsch Hadorn et al., 2008; Klein, 2004; Maasen and
Lieven, 2006; Mobjörk, 2010; Vandermeulen and Van Huylenbroeck,
2008). This rather pragmatic approach finally superseded earlier
attempts to define transdisciplinarity in terms of a new paradigm for
the unity of science (cf. Jantsch, 1970; Max-Neef, 2005). However,
although there is widespread agreement on what distinguishes disciplinary, multidisciplinary, and interdisciplinary forms of research (Kessel and
Rosenfield, 2008; Miller et al., 2008; Russell et al., 2008; Stokols et al.,
2008), the consensus on how transdisciplinarity differs from the latter
is somewhat less pronounced.
Generally the differentiation occurs on the level of cooperation
(see references above). While transdisciplinarity thus differs from
interdisciplinarity in that it involves cooperation between researchers
and ‘practitioners’, Mobjörk (2010: 868) argues that both are equal
with respect to the motives (“[b]oth instrumental and critical”) and
the role of integration (“[i]ntegration is pivotal and a shared problem
definition is needed”). Other authors however emphasize that transdisciplinarity is not necessarily “characterized by an explicit engagement with society” (Miller et al., 2008). They rather emphasize that
where interdisciplinarity still relies on disciplinary borders in order to
define a common object of research in “areas of overlap (…) between
disciplines” (Russell et al., 2008: 460), transdisciplinarity truly “transgresses or transcends” (ibid.) them (see also Horlick-Jones and Sime,
2004; Repko, 2012). In doing so it develops “shared conceptual and
methodologic frameworks” (Stokols et al., 2008: 79) that have “the
potential to produce transcendent theoretical approaches” (Klein, 2008:
117). As Miller et al. (2008) underline, transdisciplinarity in this spirit
also “transcends entrenched categories to formulate problems in new
ways” (Miller et al. (2008): 3).
2.3. Transdisciplinarity is a Research Approach, Not a Theory, Methodology
or Institution
In the early days of the discourse the idea of developing transdisciplinarity as a theoretical principle that would profoundly impact
and alter disciplinary epistemologies was still deemed promising. Participants of the above mentioned 1970 OECD conference envisioned
transdisciplinarity as a set of axioms to be shared by the different
academic disciplines (Apostel et al., 1972). More than 20 years later
Gibbons et al. (1994) believed that “transdisciplinary knowledge
develops its own distinct theoretical structures” (ibid.: 5). Yet at the
same time they already ascertained that “Mode 2 shows no particular
inclination to become institutionalized in the conventional pattern”
(ibid.: 10). It was the 2000 Zurich Conference on transdisciplinarity
that adopted and popularized a more pragmatic approach. Emphasizing
its ties to the context (of a “real-world” problem setting), participants
agreed that transdisciplinarity “is an additional and mainly demand
driven form of research” (Klein et al., 2001: 8). The Zurich approach of
shifting the discourse on transdisciplinarity from science-theorydriven deliberations to asking what this new way of doing science
means in (research) practice was widely adopted. Russell et al.
(2008), for example, notice that transdisciplinarity “is a practice, not
an institution” (ibid.: 470) and Klein (2004) states that it is “simultaneously an attitude and a form of action” (ibid.: 521).
An important aspect in this respect is emphasized by Miller et al.
(2008). In unfolding their concept of “epistemological pluralism”,
they stress that “internal reflexivity” (ibid: 4) needs to be an essential
part of transdisciplinary research. In fact it can be alleged that bringing
reflexivity into processes of knowledge production is both the claim
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
and main purpose of the transdisciplinary research practice. The arguments are (again) found in the conceptualizations of the two key
references of the transdisciplinarity discourse—post-normal science
and Mode 2: The complexity of a societal problem requires moving
beyond the sole reign of scientific expertise in policy formulation;
yet within such an extended peer community setting (read ‘postnormal science’) or an agora of public deliberation (read ‘Mode 2’),
reflexivity—as a prerequisite for accountability–is required to distinguish hard facts from evidence (Frame and Brown, 2008; Funtowicz
and Ravetz, 1997; Gibbons et al., 1994; Klein, 2004; Mobjörk, 2010;
Ravetz, 2006).
2.4. Transdisciplinarity Aims at Enabling Processes of Mutual Learning
between Science and Society (i.e. Between Scientific and Extra-Scientific
Actors)
Closely related to the idea of reflexivity is the notion of ‘mutual
learning’ between scientists and external stakeholders in processes of
joint problem solving.2 First introduced as a basic principle of transdisciplinarity by Scholz (2001), mutual learning denotes a process of
“exchange, generation and integration of existing or newly developing
knowledge in different parts of science and society” (ibid.: 118). Since
then many authors have considered some kind of “symmetry of enlightenment” (Maasen and Lieven, 2006: 404) between scientists and stakeholders to be both the key component and the ultimate goal of a
transdisciplinary research process (Aeberhard and Rist, 2009; Maasen
and Lieven, 2006; Miller et al., 2008; Pohl, 2008; Roux et al., 2006;
Russell et al., 2008; Stokols et al., 2008).
The idea of mutual learning comes with an egalitarian impetus
that in practice all too often is retarded by power asymmetries
between the participating actors (see Nowotny et al., 2001). For it
to actually occur a number of conditions have to be fulfilled that
are, as a rule, largely unswayable for those who are in charge of the
process. In order to realistically assess the possible outcome of a
mutual learning process some authors therefore emphasize the need to
understand and to “acknowledge the power relations between various
actors, their possibilities to be active participants, and the role they
play in relation to researchers” (Mobjörk, 2010: 870). Mobjörk
approaches this issue practically in suggesting that “consulting” and
“participatory” transdisciplinarity” (ibid.) be differentiated. Whereas in
the former, societal actors only “have the role of responding and reacting
to the research”, the latter conceives them as partners in a joint research
process in which their knowledge is “equally valuable to scientific
knowledge” (ibid.).
2.5. Integration is The Major Cognitive Challenge of Transdisciplinarity
The importance of integration in transdisciplinary research has
been emphasized by a large number of recent publications (cf.
Bechmann et al., 2009; de Vries and Petersen, 2009; Frame and Brown,
2008; Gray, 2008; Kessel and Rosenfield, 2008; Russell et al., 2008;
Stauffacher et al., 2008; Stokols et al., 2008; Turnpenny et al., 2009;
Wickson et al., 2006). In fact, in specific contexts of application—like
sustainable development or environmental management—terms like
‘integrative research’ or ‘integration sciences’ are often used instead of
or synonymous with transdisciplinarity (Dovers, 2005; Hirsch Hadorn
et al., 2010; Ling et al., 2009; Lövbrand et al., 2009; Macleod et al.,
2008; Strang, 2009; Weichselgartner and Kasperson, 2010; Winder,
2003). Here, the need for and the difficulties of integration are often
based on the “limitations and conditionality of the different disciplinary
2
As Farrell (2011) notes, speaking of ‘problem solving’ “reflects a classically modernist, industrial problem solving mindset” which ignores that “wicked problems are,
by definition, unsolvable conundrums for the modernist planner” (ibid.: 75). We share
this critical argument. In fact, we consider reflecting on the transitory nature of ‘solutions’ to societal problems as being one of the prime tasks of transdisciplinary research.
3
basic constructions of the world” (Baumgärtner et al., 2008: 388) or on a
still prevalent “dualistic intellectual paradigm in which ‘nature’ is perceived as separate from human ‘culture’” (Strang, 2009: 3, see also
Becker, 2012).
In the context of interdisciplinarity Repko (2012) defines integration
as “the cognitive process of critically evaluating disciplinary insights and
creating common ground among them to construct a more comprehensive understanding” (ibid: 263). Since transdisciplinarity differs from
interdisciplinarity by reaching out to extra-scientific knowledge (see
above), this definition, however, cannot be immediately transferred to
the former. In the next section, we will thus define integration more
generally as the cognitive operation that establishes a novel, hitherto
non-existent connection between distinct entities of a given context.
Some authors hold that although integration “is essential in transdisciplinarity”, it “ought not to be placed in centre” (Mobjörk, 2010:
868). Along with his observation of an emergent, self-contained discourse on integration, Mobjörk cautions that focusing on integration
could lead to “separating methodologies from epistemologies” (ibid.:
867)—the development and widespread application of integrated assessment (see Frame and Brown, 2008, and references therein) being
but one prominent example of this trend. When, however, we relate
integration not only to different bodies of knowledge but also to other
levels or entities, it might well serve to more clearly characterize transdisciplinarity (see also the next section). Zierhofer and Burger (2007)
for example distinguish three types of knowledge integration: thematic
integration of knowledge, problem- or product-oriented integration of
knowledge, and social integration (ibid.: 66f). The last type—although
it originally referred to the different forms and qualities of knowledge
of both scientific and extra-scientific actors—already indicates how
the notion of integration in transdisciplinarity might be extended: It
also needs to address the fact that in participatory research the various
actors have to become involved as persons who bring distinct interests,
roles, and practices of communication. These additional levels of integration are frequently discussed in the current literature on transdisciplinarity (Castán Broto et al., 2009; Dale et al., 2010; Felt, 2010;
Kessel and Rosenfield, 2008; Margles et al., 2010; Roux et al., 2006;
Wardekker et al., 2008). Integrative forms of communication receive
particular attention in this respect. Strang (2009), for example, asserts
that “to achieve forms of communication that not only allow bridge
building between disparate disciplines, but also translate findings into
widely accessible forms” (ibid.: 9) is a major challenge. Klein emphasizes in referring to Després and colleagues that “[r]ational knowledge
(…) comes out of not only ‘what we know’ but ‘how we communicate’
it” (Klein, 2004: 521).
2.6. Transdisciplinarity Involves, As a Rule, Disciplinary Practice
Although they do not always make it explicit, most scholars take
for granted the fact that transdisciplinarity (or any other form of
cross-disciplinary collaboration) does not mean replacing established
disciplinary practice. Klein (2004), for example, states that “[o]f
necessity, transdisciplinary work is based on disciplinary practice” and
that although it was distinct, “it is complementary” (ibid.: 524)—an
opinion also shared by those authors who follow the idea(l) of some
form of unity of knowledge (cf. Lawrence and Després, 2004; MaxNeef, 2005; Nicolescu, 2008). Discussing flaws in the current systems
of higher education, Russell et al. (2008) call on universities “to focus
on building intellectual capacity” and they advise that “[s]trong intellectual capacity is best served by combining disciplinarity and transdisciplinarity.” (ibid.: 469). Their argument suggests that disciplinarity
and transdisciplinarity mutually enrich each other.
In fact, by its very nature any form of cross-disciplinary endeavor
serves the participating disciplines in that it challenges the scope of
their respective knowledge, methods, and theories. In this sense,
cross-disciplinary collaboration may function as a driver for disciplinary
innovation by questioning and eventually reshaping internal borders. By
4
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
focusing on societal problems, transdisciplinarity in particular can work
as a search engine for new research questions or fields of application that
do not readily emerge from following the internal logic of disciplinary
progress. Reflecting on the borders between idiographic and nomothetic
research, Krohn (2008) states that transdisciplinarity is a mixture of both
and explains: “If a project is excellent in solving a highly idiographic case
this is a welcome scientific contribution to local politics. Its value is not
downgraded if there is no considerable contribution to theory. If, in
turn, causal analysis promises a theoretical breakthrough without immediate payoff for practical solutions this is also acceptable." (ibid.: 381f).
As we will discuss later, this possible contribution to both societal and
scientific progress suggested here is a constitutive feature of our overarching concept of transdisciplinarity.
2.7. Research for Sustainable Development Requires a Transdisciplinary
Approach
Since the concept of sustainable development was introduced in
the early 1990s, scholars have consistently called for a new form of
research that would be able to provide solutions to the complex problems it poses. It can in fact be argued that the development of ideas
like post-normal science and Mode 2 was influenced, or at least pushed,
by the sustainability debate. When in the wake of these two eminent
landmarks the discourse about transdisciplinarity gained momentum
in the 1990s, it soon became evident that a major application of this
new mode of knowledge production was sustainability (Klein et al.,
2001). Since then, most scholars have agreed that dealing with
problems of sustainable development requires a transdisciplinary
approach (Baumgärtner et al., 2008; Boserup, 2010; Farley et al., 2010;
Frame and Brown, 2008; Kajikawa, 2008; Kauffman, 2009; Komiyama
and Takeuchi, 2006; Schneidewind, 2010; Steinfeld and Mino, 2009;
Vandermeulen and Van Huylenbroeck, 2008; Weinstein, 2010).
In recent years, however, besides the idea of ‘transdisciplinary
research for sustainable development’ the notion of ‘sustainability
science’ has frequently been used. Although both terms are often
used synonymously, some authors argue that sustainability science
is an evolving discipline in its own right (Frame and Brown, 2008;
Kajikawa, 2008; Kauffman, 2009; Komiyama and Takeuchi, 2006;
Steinfeld and Mino, 2009; Ziegler and Ott, 2011). These authors
hold that sustainability science is to become some kind of ‘super- or
supra-discipline’ that “will have its own specific body of knowledge
and framework with which to address sustainability issues, even while
retaining relationships with other disciplines.” (Kajikawa, 2008: 216).
Consistently, albeit enigmatically, Kajikawa defines sustainability science as “a distinct discipline engaged in a transdisciplinary effort arching
over existing disciplines” (ibid.: 216).
The need to create a new genuine discipline is, however, hardly
justified in the relevant literature (for a remarkable exception in a
related field see Bammer, 2008). Moreover, these efforts seem to roll
back some 20 years of instructive debate on the necessity of new forms
of producing knowledge to address problems that defy disciplinary
confinement. As Ziegler and Ott (2011) argue, interpreting sustainability
science as a distinct discipline allows one to address the important issues
of evaluation and quality assurance in a meaningful way. From a transdisciplinary perspective these issues are related to the joint research process and the contribution of its outcomes in solving a sustainability
problem. Yet, this new focus on evaluation and quality assurance
requires new forms that cannot be found by reverting to established
disciplinary standards (Bergmann et al., 2005).3
3
It has to be kept in mind here that transdisciplinarity builds upon disciplinarity and
thus also on the standards of good scientific practice defined therein. Enabling cooperation between science and society for addressing real-world problems adds an additional level of evaluation and quality assurance that by its very nature involves
extra-scientific criteria.
3. A Conceptual Model of Transdisciplinarity
Appraising the last section, we can now enrich the definition of
transdisciplinarity which we introduced above: Transdisciplinarity is
a reflexive research approach that addresses societal problems by
means of interdisciplinary collaboration as well as the collaboration
between researchers and extra-scientific actors; its aim is to enable
mutual learning processes between science and society; integration
is the main cognitive challenge of the research process. Within the
limits of our analysis we hold that this definition reflects a broad
consensus among scholars of transdisciplinarity. However, it does
not immediately provide the sort of practical guidance that supports
researchers, program managers, and donors in appreciating the
problem-specific challenges of transdisciplinary endeavors. In this
section we will thus present a conceptual model of transdisciplinarity
that could serve this purpose. It assimilates the main features of the
shared framework of transdisciplinarity outlined in the previous
section.
The first impetus for developing the model occurred in the course
of a project on the identification and description of quality criteria for
transdisciplinary research (cf. Bergmann et al., 2005). The project was
part of a research program run by the German Federal Ministry of
Research ("Social–Ecological Research"). Its overall aim was to provide
this program and the transdisciplinary research community with adequate tools for evaluating research proposals and results. The criteria
were developed by empirically analyzing a selection of concrete transdisciplinary research projects. The analysis team included experts
from various disciplines, from science and technology studies, and
from the sectors of society that were addressed by the selected research
projects. Halfway through this development process the team agreed
that it would be helpful to have a picture of what were the most important phases of an ideal transdisciplinary research process in terms of
quality management and assessment. Having proved useful for the
further criteria development the ‘picture’ subsequently evolved into
the first version of our “model of the reflexive transdisciplinary research
process” (Bergmann et al., 2005: 17–19; Jahn, 2005: 34 ff.). Since then
the model has been successively refined while working on concepts
and methods for transdisciplinary research and by applying it to the
design of a number of concrete research projects as well as to academic
teaching.4
The model builds upon a basic proposition: In practice, developing
solutions for societal problems always means and requires linking
these problems to gaps in the existing bodies of knowledge, that is, to
scientific problems. Seemingly self-evident, this proposition, however,
allows us to conceptualize the contributions to societal and scientific
progress as the two epistemic ends of a single research dynamic. Moreover, from this perspective the two approaches to transdisciplinarity
that are distinguished in the current literature (cf. Jahn, 2008; Pohl,
2008) appear as the two ends of a spectrum: At the one end we have
the life-world approach, in which society employs science to provide
practical solutions for concrete problems; at the other we find the
inner-scientific approach, in which science, while explicitly relating to
societal problems, mainly pursues its own generic goals (production
of new knowledge, methods, models, and theories). With this background we can now develop our conceptual model of transdisciplinarity
(Bunders et al., 2010; Jahn, 2008; Jahn and Keil, 2006a). It distinguishes
three phases of an ideal transdisciplinary research process (see Fig. 1).
In the first phase societal and scientific problems are linked to form
a common research object—a process we refer to as ‘problem transformation’ (Becker, 2002; Hirsch Hadorn et al., 2008; Jahn and Keil,
2006b). Problem transformation basically consists of two consecutive
4
An example for the frequent use of the model in teaching is Daniel Lang's regular
seminar "Inter- and transdisciplinary Cooperation" in the frame of the Minor "Sustainable Humanities" at Leuphana University Lueneburg, Germany.
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
Societal Problems
Contested values, lack of orientation
and transformation knowledge,
institutional specialisation, limits to
knowledge transfer…
Societal Discourse
Administration, institutions, NGOs,
corporations, political sphere…
Formation of a
Common Research Object
Scientific Problems
Problem Transformation
1
Production of New Knowledge
(Interdisciplinary Integration)
5
Contested knowledge, lack of
(system) knowledge and methods,
disciplinary specialisation, limits to
transfer of new knowledge…
Scientific Discourse
2
Institutions of higher education,
non-university research facilities,
industrial research…
3
Results for Societal Praxis
Strategies, concepts, measures,
prototypes, technologies…
Transdisciplinary Integration
Evaluation of new knowledge for its
contribution to societal and scientific progress
Results for Scientific Praxis
Methodical and theoretical
innovations, new research
questions…
Fig. 1. A conceptual model of transdisciplinarity (modified according to Jahn, 2008). The numbers indicate the three phases of the ideal transdisciplinary research process (see text
for explanations).
steps. First, the given societal problem is transformed into a boundary
object. Boundary objects are the very prerequisites for enabling cooperation in a heterogeneous group of actors: they are open and flexible
enough to accommodate individual perspectives and meanings while
at the same time maintaining an identity that is recognized by all
parties involved (Star and Griesemer, 1989). One example of an
abstract boundary object is a concept like ‘biodiversity’; a concrete
boundary object, in contrast, can be, for example, a map of a specific
nature conservation area. In the second step boundary objects are
transformed into epistemic objects by means of developing or applying
theories or concepts. These epistemic objects are, in turn, the basis from
which research questions are derived. Describing the interactions
between agriculture, forestry, tourism, and wildlife in a local nature
conservation area within the framework of a social–ecological system
(cf. Berkes et al., 2003; Hummel et al., 2011) is an example of an epistemic object in transdisciplinary research. Team formation is essential at
the very beginning of this first phase (see also below). In order to foster
cohesion and commitment throughout the transdisciplinary research
process it is mandatory that all parties involved participate in problem
transformation. Likewise, creating epistemic objects in a joint effort of
the whole team is crucial in allowing for an integrative design of the
research process (Bergmann et al., 2010: 117 ff).
We note that problem framing (Rossini, 2009) and problem structuring (Scholz et al., 2009) are similar approaches to the deliberate process
of making a societal problem accessible for dedicated research. However,
we favor the notion of problem transformation, because what happens
in this process is, in most cases, not a unique mapping of a societal
onto a corresponding scientific problem; instead, as knowledge itself
changes (both as regards structure and meaning) when transferred
from one context to another, so too does a problem when displaced
from the world of needs, interests, and values into the realm of scientific
rigor and objectiveness; in other words, a solution to the identified
scientific problem is not imperatively a possible solution to the original
societal problem. A reflexive process is thus needed to help
maintain close ties between scientific and societal problem descriptions
throughout the whole research process. Only in this way can (diverging)
expectations among participants (both from science and society) as
regards the desired outcomes of research be managed successfully.
Whenever a societal problem is taken as the starting point for
research, a problem transformation of some kind takes place. Making
this transformation consciously is one feature that, in our model,
distinguishes transdisciplinarity from other forms of collaborative
research. Whether scientists and societal actors cooperate to find a
shared description for a specific problem or a team of scientists
derives its research questions by transforming socially contested issues
into epistemic objects—e.g. by means of the analysis of discourses or
socio-empirical methods—is, to begin with, secondary. What is decisive
is that it happens in a reflexive, methodically-guided process that is able
to balance the tensions that, as experience teaches, tend to occur most
prominently in this initial phase—when the different individual or institutional interests, goals, and norms or the disciplinary backgrounds of
the cooperating participants clash for the first time. The extent to
which a team succeeds in this effort crucially determines the success
of the collaborative endeavor. There are meanwhile a number of strategies and procedures available for implementing problem transformation in research practice (Bergmann et al., 2010; Hirsch Hadorn et al.,
2008).
The second phase of our ideal transdisciplinary research process is
characterized by the production of new knowledge (center part of
Fig. 1). As transdisciplinarity is based on disciplinary practice, what
happens here is an interplay of specialized work in sub-teams (e.g.
including both researchers and extra-scientific actors) and dedicated
stages of integration of the epistemologically pluralistic (Miller et al.,
2008) outcomes of this work. We call this process ‘interdisciplinary
integration’ and thus strictly define interdisciplinarity as an integral
part of transdisciplinarity in our model. In other words, while transdisciplinarity sets the frame for a research dynamic that couples societal
and scientific progress, interdisciplinarity is the science driven process
of generating the new knowledge that fuels this progress. In this way,
we propose a structural distinction between the two modes of research.
6
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
Table 1
Application of the conceptual model of transdisciplinarity to a concrete research project.
Time specifications relate to the period of project implementation (2005–2008) throughout
the table.
Application of the conceptual model
Starting point of the project
The project transpired following observations that the increasing occurrence of
active ingredients of pharmaceuticals for human use (API) in waters was an
aging scientific fact. Notwithstanding, there was little meaningful data on
adverse effects for wildlife and humans at measured concentrations available.
Correspondingly, effective measures for reducing APIs in waters (e.g. in the
context of drug authorization) were found to be lacking. Moreover, a cursory
media analysis revealed only sporadic public awareness of the findings and
their main cause (i.e. excretion of drug residues into domestic sewage). In
order to align the project, the decision was thus taken to start off by surveying
the societal problem perceptions.
Phase 1—Problem transformation
Step 1.1: Framing the societal problem
By means of interviews with stakeholders (representatives from medical and
pharmacy associations, pharmaceutical industry, public health funds, and
water management) and other socio-empirical methods (focus groups with citizens/patients, physicians, and pharmacists) the following societal problem description was derived:
Water as the most fundamental life sustaining natural resource should be free
from any pollution. APIs are of particular concern as they are designed to have
physiological impact. Whether APIs in waters actually pose a risk to wildlife
and humans is highly contested. Pharmaceutical products are associated
with high individual and social benefits. Measures for keeping APIs off waters
should not compromise these benefits.
The aim of this step was not to elicit a consensus but to define a frame containing
the most common societal perspectives on the issue. In fact, the given problem
description conveys two major conflicts: (1) A conflict of knowledge (Do APIs
in waters actually pose a risk to wildlife and humans?), and, (2), a fundamental
conflict of values (water protection vs. the quality of health care). The issue at
hand was thus classified as a ‘type 4’ or ‘wicked’ problem (see text for explanations). Therefore, an early decision for a strong stakeholder involvement was
taken (four dialog boards).
Step 1.2: Relating the societal problem description to scientific knowledge
In workshops with experts from pharmacology, eco-toxicology, environmental analysis, environmental engineering, water management, sociology, and risk research the
societal problem description was related to the available scientific knowledge:
Water that is free from contaminants does not exist; water purity is related to the
level of pollution and the given measuring accuracy. For a number of reasons, the validity of current risk assessments for APIs in waters is principally limited. The properties of today's drugs make their partial excretion and slow degradation in the
environment unavoidable. Environmental engineering today provides no single
technology which completely eliminates all APIs from domestic sewage or drinking
water sources.
Given these insights, the classification of the issue as a ‘type 4’ problem was confirmed.
However, there was consensus among experts that the knowledge conflict cannot be
solved in the short run by collecting more data. This led to the decision to focus the project on strategies to reduce the occurrence of APIs in waters which were sensitive to
the conflict of values—a decision with immediate consequences for team building: Instead of emphasizing the expertise on environmental analysis or toxicology the team
was centered on capacities for strategy development. Note that the knowledge conflict
precluded a simple top-down regulatory solution of the problem.
Step 1.3: Transformation of the societal problem into a boundary object
According to the results of steps 1.1 and 1.2 the main quality of the boundary object
had to be its flexibility towards the conflict of values, i.e. the stakeholders had to be
able to identify with the boundary object such that it allowed them to commit to the
process. At the same time, the boundary object had to be concrete enough in order
to avoid a stalemate. Drawing on the results of the two preceding steps, stakeholders
and scientists created the following boundary object at the first dialog board:
The occurrence of APIs in communal water cycles is an undesirable side effect of the
normal mode of operation of the health care system.
By relating to the boundary object, the participating stakeholders and researchers
finally specified the project goal to be the development of such strategies for
reducing the occurrence of APIs in waters that do not impair the quality of health
care (a strategy was defined to consist of a set of harmonized actor-specific reduction
measures). On this basis, stakeholders defined criteria for minimal and maximal societal success of the project (a catalog of reduction measures and an integrated reduction
strategy, resp.).
Step 1.4: Transformation of the boundary object into epistemic objects
In this final step of the first phase the project team convened to transform the
boundary object into an epistemic object. For this purpose, the concept of
systemic risks (OECD, 2003) was applied. Systemic risks refer to unintended
processes or events which, as a result of interconnections between systems, have
Table 1 (continued)
Application of the conceptual model
negative impacts far beyond their points of origin (ibid.). Adapting this concept to
intended processes (Keil et al., 2008), the following epistemic object was created:
The prescription of drugs for the prevention and cure of diseases produces systemic
risks for ecological (river basins) and socio-technical (water supply) systems.
By referring to the project goal and by applying the systemic risk concept the project
team formulated specific research questions related to risk governance, risk perception, and risk communication (Renn and Keil, 2008). On this basis, the criteria for minimal and maximal scientific success of the project were determined (initiating a new
research focus on reduction measures and a general concept for a systemic risk governance, resp.).
Phase 2—Interdisciplinary integration
Step 2.1: Clarification of the roles of researchers and stakeholders
At the second stakeholder dialog board the roles of researchers and stakeholders
were clarified on the basis of the project goal, the research questions and the
expectations on project outcomes (e.g. stakeholders defined themselves not
only as representatives of particular interests but also as experts). This
clarification was a prerequisite for the successful integration of science and
society over the course of the project. It was also agreed upon at this meeting
to regularly revisit the epistemic object, project goal, boundary object, and
societal problem description as new knowledge became available (e.g. some
stakeholders opposed to using the term ‘risk’; this later led to introducing the
precautionary principle as an argument for implementing reduction strategies).
Step 2.2: Design of an integration concept
The core of the integration concept was the life cycle approach of a
pharmaceutical product. It supported epistemic, communicative and socialorganizational integration by differentiating and linking areas for the development of reduction strategies: drug development, handling of drugs, and disposal
of drug residues via excretion into domestic sewage. For each of these three
areas a dedicated sub-group of researchers from the project team was appointed.
A fourth sub-group was set up to investigate legal, institutional, social, and political conditions for a joint reduction strategy. In defining areas of expertise and
responsibility for the implementation of reduction measures, the life cycle approach further enhanced the clarification of the role of stakeholders.
Step 2.3: Implementation of the integration concept
Using a variety of methods the three project sub-groups each developed a reduction strategy for their life cycle phase. Stakeholders were invited to comment on
these strategies. In order to assess the possible impact of each strategy in terms
of the project goal, a multi-criteria analysis was carried out. The criteria and their
weights were determined jointly between stakeholders and researchers at the
third dialog board. Results showed that none of the single strategies performed
satisfactorily according to the chosen criteria. Using the knowledge produced
by the fourth project sub-group an integrated reduction strategy was developed
in a joint effort by the whole project team.
Phase 3—Transdisciplinary integration
Step 3.1: Assessment of integrated results
The fourth stakeholder dialog board was focused on the joint assessment of the
integrated reduction strategy. For this purpose a scenario approach was used.
As a result of the assessment the integrated strategy was complemented by a
‘seed strategy’: for each life cycle phase, a few targeted reduction measures
were identified; they were designed to activate a bottom-up process of joint societal action to reduce the occurrence of APIs in waters (in fact some of the participating stakeholders agreed to pioneer). The potential of the project outcome
to contribute to societal progress was evaluated via a questionnaire procedure
with the participating stakeholders (in terms of the defined success criteria but
also with respect to broader aspects such as changes in problem perception).
The intended contribution to scientific progress (cf. step 1.4) was put to the
test at an expert conference organized by the project team.
Step 3.2: Assembly of products for science and society
As the main product of the project for societal praxis the project team and the
stakeholders edited a guide that presented the state of knowledge and the
reduction strategies (ISOE, 2008). The guide addressed decision-makers in relevant organizations, companies, politics, and administration. In order to support
the systems approach of the project its scientific results were prepared as a series
of articles in peer-reviewed journals and as an edited book that introduces the
concept of a Green and Sustainable Pharmacy (Kümmerer and Hempel, 2010).
Impacts of the project on the societal and scientific discourses
The project had two major impacts on the societal discourse about APIs in waters.
First, local authorities implemented single reduction measures with reference to
the project outcomes. Second, the German Federal Ministry of Health issued an
order that requested the Federal Environment Agency to draft a positioning
with respect to options for implementing the reduction strategies proposed by
the project. The project impacted the scientific discourse by having initiated
several follow-up research projects that investigated different aspects of the reduction strategies.
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
Whether interdisciplinarity then still means relying on disciplinary
boundaries (cf. Russell et al., 2008) or requires ‘truly transgressing’
(Stokols et al., 2008: 79) them is not predetermined but will be entirely
dependant on the nature of the problem at hand (that is to say, whether
disciplinary boundaries are left behind to create higher level conceptual
frameworks or theories will be emergent to the specifics of a concrete
transdisciplinary research process). Rather than finding the appropriate
label, to our mind, it is thus decisive for both planning and appraising
transdisciplinarity to assess early on the size of the integration task at
hand. As we will see later, a differentiation of problem types can effectively support such an assessment.
In the third and final phase of our ideal transdisciplinary research
process the integrated results of the previous phase are assessed
(lower part of Fig. 1). According to our basic proposition this assessment asks for their possible contribution to both societal (validity and
relevance for the original real-world problem) and scientific progress
(new insights within and beyond disciplines). As well as applying standardized or innovative strategies (cf. Bergmann et al., 2010) the assessment proceeds practically as a process of mutual critique among all
process participants. Yet critique, by its very nature, is disintegrating.
Instead of weakening the process, however, it becomes the prerequisite
for materializing what is frequently referred to as the ‘added value’
(Jahn, 2008: 33) of transdisciplinarity: Having been subjected to scrutiny
from different epistemological perspectives, the results undergo a
second-order integration that potentially makes them better suited to
the needs of both scientists and societal actors. We call the process of
assessment of integrated results their (partial) disintegration by mutual
critique and their second‐order integration as ‘transdisciplinary
integration’.
Finally, transdisciplinarity in our model intervenes both in the societal and scientific discourses about the issue at stake. It does so by means
of targeted or non-targeted knowledge transfer by both scientists and
societal actors (see center left and right part of Fig. 1). The impacts this
intervention might have—e.g. in terms of the implementation of strategies, amended legislation or innovative technologies—eventually give
rise to a new transdisciplinary research process that starts with a modified understanding or framing of the initial problem.
Table 1 illustrates how the three phases of our model materialize
in a concrete transdisciplinary research project. It was one of the
first projects that was planned and implemented by applying the
conceptual model (Keil, 2010; Keil et al., 2008). The table serves to
illustrate the basic rationale applied in each phase of the transdisciplinary
research process. It does neither aim to present a full account nor an evaluation of the project. The nine steps of the table which detail the three
phases introduced above can serve as orientation for the design of any
transdisciplinary project. They are, however, not meant to be canonical
but rather have to be adapted to the context of the particular societal
problem under investigation.
We have frequently referred to our model as representing an ideal
transdisciplinary research process. By this we mean two things. First, as
a matter of course, the three phases in practice do not always linearly
lead to the final conclusions of a project. Rather, as a result of the assessment in phase three it might become necessary to repeatedly revisit
phase two (or even phase one). Therefore it is pivotal that an integration concept that provides for such an iterative approach is developed
at an early stage in any transdisciplinary endeavor. Second, not all
aspects of our ideal process will be given equal weight in research practice. It is, for example, possible that, depending on the problem, either
the contribution to societal or scientific progress receives priority. In
fact, looking at Fig. 1 one can distinguish two loops that each characterize one of the two ends of the spectrum of transdisciplinary approaches
which we introduced above: Moving from the upper left corner through
the middle column and back corresponds to the life-world approach
which focuses on practical solutions (‘left loop’); in the same way,
starting from the upper right corner corresponds to the innerscientific approach which primarily aims at new scientific insights
7
(‘right loop’). Now from what we said before, it becomes immediately
clear that the size of the integration task crucially depends on how
much weight one or the other approach receives in a given case. As
we will show later, this will be the basis for illustrating how our
model can be used as a classification tool for different approaches to
transdisciplinarity.
The discourse on transdisciplinarity and knowledge integration in
ecological economics also draws upon this conceptual juxtaposition.
Baumgärtner et al. (2008: 387), for example, state that ecological economics "requires both, the reference to the complexity of real-world
experience and its aspects beyond purely rational construction (…),
as well as the reference to the rational construction of the mind,
which turns out to be crucial in particular for interdisciplinary integration". Notwithstanding, an elaborate concept for transdisciplinarity
does still not exist in ecological economics. Transdisciplinary knowledge integration, however, could help exploiting the strong conceptual
and methodological basis of ecological economics for advancing societal
knowledge processes. Along these lines, we thus propose to examine to
what extent our model can help to strengthen the transdisciplinary
foundation of ecological economics.
3.1. A Multi-dimensional Perspective on Integration
In the second section of this article we identified integration to be
the main cognitive challenge of transdisciplinarity. We defined integration to be the cognitive operation that establishes a novel, hitherto
non-existent connection between distinct entities of a given context.
Entities can be, for example, specific knowledge structures, data or
mind sets, theories, models, paradigms, norms, values, interests, linguistic forms, and the roles of actors and institutions. More precisely,
in our model of transdisciplinarity we understand integration as a
process that leads to a change in the structure and organization of a
problem context by extending and constraining both the relations
between its entities and their respective characteristics (Becker and
Keil, 2006). To achieve this, processes of integration necessarily have
to be preceded by processes of differentiation, or, practically speaking,
identifying, explicating and recognizing differences is the prerequisite
for successful integration.5 In our model, differentiation and integration
are conceived to be alternating actions throughout the transdisciplinary
research process. Using this as background we propose a multidimensional perspective to integration by distinguishing between
three levels (Becker and Keil, 2006; Bunders et al., 2010):
— On the epistemic level, different bodies of knowledge have to be
demarcated and interlinked; this applies to disciplinary or specialized
scientific knowledge as well as to scientific and extra-scientific
knowledge; in practical terms, this means understanding the
methods, notions, and concepts of other disciplines and recognizing
and explicating the limits of one's own knowledge;
— On the social-organizational level, different interests or activities
of participating researchers, subprojects, and larger organizational
units have to be explicated and connected or, where possible,
reconciled; in most cases the latter will be a matter of mediating between insisting on hard facts and accepting evidence that supports
useful solutions‐a process that is often affected by the expediencies
of science policy;
— On the communicative level, different means of linguistic expression
and communicative practice have to be differentiated and related or
synthesized; the aim is to establish some kind of a common
language that advances mutual understanding and agreement (for
example as an essential prerequisite for joint publications).
5
Addressing a societal problem in transdisciplinary research means addressing conflicts of knowledge or values. Successful integration is a prerequisite for that the problem context can be changed in a way such that these latent, emerging, or open conflicts
have become alleviated, solved, or manageable.
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
Distinguishing these three levels allows for the development,
selection, and application of dedicated strategies to cope with the
associated integration tasks (for a compilation of strategies see
Bergmann et al., 2010). As we saw in the second section, the importance
of the epistemic and communicative levels is emphasized by a number
of scholars in the field. In research practice and science policy, however,
the social–organizational level is often neglected or undervalued—
regardless of the fact that it is of special importance in particular at
universities with their strictly disciplinary career paths and orders of
knowledge. Transdisciplinarity requires an uncommon willingness
of individual scientists to learn and to think outside the disciplinary
box. This willingness, in return, crucially depends on the extent to
which individual interests are recognized and supported.
3.2. Application of the Conceptual Model as a Classification Tool
So far, we have not addressed the issue of participation. In our
model certain characteristics of the problem decide on if and how
extra-scientific actors are to be involved in the transdisciplinary
research process. Therefore, characterizing different types of problems
allows us to use our model as a tool for classifying different approaches
to transdisciplinarity. To do so, we revert to the typology of information
of the U.S. Committee of Scientists (1999: 131) which allows one to
distinguish four types of problems according to the strength of the
agreement on knowledge and values. The notion ‘value’ here refers to
the normative question ‘What should we do?’ (cf. Max-Neef, 2005: 8)
and thus represents the entire complex of societal and political deliberation on the goals of a problem intervention.
Now transdisciplinarity, in focusing on societal problems, in general
aims at producing three types of knowledge (cf. Becker, 2002): the
knowledge involved in the understanding of an issue (system knowledge), that required for determining the possibilities and boundaries
of decision-making (orientation knowledge), and knowledge of the
ways and means of practically realizing such decisions (transformation
knowledge). Assuming that by definition the latter is lacking in all
cases—otherwise we would not have a problem to deal with in the
first place—we can differentiate between the four possible problem
types in terms of the need to produce specific knowledge by means of
dedicated transdisciplinary research (see Fig. 2) 6:
1. Where the agreement on knowledge and values is high, what is
mostly needed is transformation knowledge; to generate this
knowledge an approach to transdisciplinarity that mainly runs
through the ‘left loop’ of our general model (see Fig. 1) is adequate;
here, the demands for integration are relatively low as the existing
bodies of knowledge are deemed sufficient in addressing the problem, and bargaining orientation knowledge is likely to be consensual
due to high agreement on values; the participation of external stakeholders, for example in the phases of product design or assessment, is
recommendable but not mandatory (standard socio-empirical
methods might also do the job here);
2. When agreement on knowledge is high but low on values, orientation
knowledge is needed in addition to transformation knowledge; as
with the first case, a ‘left loop’ transdisciplinary research process is
adequate for this problem type; however, demands for integration
are increasing as the conflictual processes of negotiating the aims of
research are now expected; the same applies to the phase of assessing
the relevance of the results to societal practice; the participation of
external stakeholders in the first and third phases of the process is
mandatory here in order to increase process and outcome acceptance;
3. For the third problem type we find agreement on knowledge low,
yet high on values; what is needed here besides transformation
knowledge is thus system knowledge; mirror-imaged to the first
6
We note that the typology we present here has similarities with the framework for
contextualizing boundary work introduced by Clark et al. (2011).
Agreement on values
Agreement on knowledge
8
high
low
high
Transformation
knowledge lacking
Orientation and
transformation
knowledge lacking
low
System and
transformation
knowledge lacking
System, orientation,
and transformation
knowledge lacking
Fig. 2. Typology of problems according to the strength of agreement on knowledge and
values (modified according to the Committee of Scientists, 1999: 131).
case, an approach to transdisciplinarity that basically follows the
right loop of our model is suitable; demands for integration are
high in all three phases of the process but peak in the second
phase with the interdisciplinary generation of new knowledge;
again, the participation of external stakeholders is recommended
(particularly in the phase of the assessment of the scientific results
for societal relevance), but not mandatory;
4. For the so called ‘wicked problems’ (Rittel and Webber, 1973) the
agreement on both knowledge and values is low; correspondingly,
specific knowledge of all three types is needed; this is the ideal
case where all aspects of our model are addressed; it is here
where demands for integration are extremely high in all phases of
the transdisciplinary research process; the participation of external
stakeholders is mandatory throughout the course of research.
We are aware that this classification is still rather coarse and that
the empirical richness of transdisciplinarity lies between these four
types. Nevertheless, we believe that, given some form of problem
characterization, our model can help science and science policy to
better appraise the true efforts which a certain approach to
transdisciplinarity requires in terms of integration. Moreover, it may
provide terminological clarity in a discourse with a variety of (often
only slightly) different connotations for key terms. Finally, our general
model can be used both as an ex-ante planning and an ex-post analysis
tool for concrete transdisciplinary research projects (Bergmann et al.,
2005).
4. Conclusions
Drawing on a broad literature study, we have identified the main
features of an evolving shared framework of transdisciplinarity in
the academic discourse. In order to provide support for a more adequate appraisal of what a creative culture of collaboration that
reaches out to both science and society requires, we proposed a conceptual model of transdisciplinarity. Its foundation is to conceive of
the contributions to societal and scientific progress as the two epistemic ends of a single research dynamic. Applying a problem typology
which is based on the respective strength of agreement on knowledge
and values, we illustrated that our model can be used to characterize
four types of transdisciplinarity and their corresponding demands on
integration. Synthesizing the results of our literature analysis with the
foundations of our conceptual model, we finally propose the following general definition of transdisciplinarity:
Transdisciplinarity is a critical and self-reflexive research approach
that relates societal with scientific problems; it produces new
knowledge by integrating different scientific and extra-scientific insights; its aim is to contribute to both societal and scientific progress; integration is the cognitive operation of establishing a novel,
T. Jahn et al. / Ecological Economics 79 (2012) 1–10
hitherto non-existent connection between the distinct epistemic,
social–organizational, and communicative entities that make up
the given problem context.
Despite the ongoing development of consensus on what transdisciplinarity basically constitutes, some rather fundamental issues
still remain controversial. In order to propose directions for further
research, we briefly highlight two of them here. First, there is disagreement as to whether transdisciplinary research is a distinct new
mode of knowledge production. Analyzing transdisciplinary research
projects, Zierhofer and Burger (2007), for example, find “no single
blueprint for [transdisciplinary research] from an epistemological or
methodological perspective” and conclude that “from this point of
view [it] does not appear as a distinctively new mode of knowledge
production” (ibid.: 66). Stressing that transdisciplinarity lacks what
is constitutive for scientific knowledge production–that is the critical
assessment of new knowledge by peers—Maasen and Lieven (2006)
argue that “transdisciplinary settings allow for mutual learning but
not for joint research” (ibid.: 406). Without going into detail here,
we believe that these and similar arguments deserve careful consideration for at least two reasons: Denying transdisciplinarity the status
of a genuine mode of knowledge production would, on the one hand,
severely undermine necessary attempts to establish it inside universities. On the other hand, locating it essentially outside academia would
impair efforts to define commonly accepted quality criteria for transdisciplinary research—a tool we consider crucial for managing expectations of participating actors on how transdisciplinarity can
contribute to societal and scientific progress in working on a concrete
societal problem.
Second, the question of whether transdisciplinarity is a new mode of
governing science is a recurring topic in the discourse. In response to
the claim that transdisciplinary research should not only produce true
but also “socially robust” (Nowotny et al., 2001) knowledge, Maasen
and Lieven (2006) argue that it is mainly upon the individual researcher
to generate such quality outcome by reconciling “different disciplinary
standards and approaches, as well as different extra-scientific demands” (ibid.: 407). Assessing a corresponding general trend towards
individualization of responsibility Maasen and Lieven caution that
transdisciplinarity is a new way of governing science which incorporates “procedures of social accountability” (ibid.). This critique rightfully
highlights the fact that with a new relation between science and society,
the roles and responsibilities of scientists are fundamentally changing.
Yet these changes are neither sufficiently discussed in the literature
nor adequately reflected in research practice.
In our understanding, transdisciplinarity is more than a research
approach that is better suited to cope with the complex problems
that scientific progress itself continuously creates. Rather, it indeed
fundamentally addresses the relation between science and society.
It is interventionist in the sense that it methodically frames, structures, and organizes the societal discourse about the problematic of
an issue at stake. Next to its traditional tasks, science, in our model,
is assigned a special role: Transdisciplinary researchers have the expertise to distinguish between different forms of knowledge by
unraveling how they were produced and how they are related in
the network of interconnections of a complex issue. At its core transdisciplinarity is, as we see it, both critical and self-reflexive: It not
only systematically scrutinizes in which ways knowledge is produced
and used by different societal actors in support of their concerns; it
also methodically challenges how science itself deals with the tension
between its constitutive pursuit of truth and the ever increasing
societal demand for the usefulness of its results.
Acknowledgments
This work was in part financially supported by the German Ministry of Education and Research (contract no. 01UT1004). The authors
9
also wish to thank the three independent reviewers of this article
for their valuable comments.
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