Best Practices or Best Guesses? Assessing the Efficacy of Corporate Affirmative Action and
Diversity Policies
Author(s): Alexandra Kalev, Erin Kelly, Frank Dobbin
Source: American Sociological Review, Vol. 71, No. 4 (Aug., 2006), pp. 589-617
Published by: American Sociological Association
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Best Practices or Best Guesses?
Assessing the Efficacyof Corporate
Affirmative Action and Diversity Policies
Alexandra Kalev
University of California, Berkeley
Frank Dobbin
Harvard University
Erin Kelly
University of Minnesota
Employers have experimented with three broad approaches to promoting diversity. Some
programs are designed to establish organizational responsibilityfor diversity, others to
moderate managerial bias through training andfeedback, and still others to reduce the
social isolation of women and minority workers. These approaches find support in
academic theories of how organizations achieve goals, how stereotyping shapes hiring
and promotion, and how networks influence careers. This is thefirst systematic analysis
of their efficacy. The analyses rely on federal data describing the workforces of 708
private sector establishmentsfrom 1971 to 2002, coupled with survey data on their
employmentpractices. Efforts to moderate managerial bias through diversity training
and diversity evaluations are least effective at increasing the share of white women,
black women, and black men in management. Efforts to attack social isolation through
mentoring and networking show modest effects. Efforts to establish responsibilityfor
diversity lead to the broadest increases in managerial diversity. Moreover, organizations
that establish responsibility see better effectsfrom diversity training and evaluations,
networking, and mentoring. Employers subject to federal affirmative action edicts, who
typically assign responsibilityfor compliance to a manager, also see stronger effects
from some programs. This work lays thefoundation for an institutional theory of the
remediation of workplace inequality.
Lists
of "best practices" in diversity man-
agement
have proliferated
recently.
to the Presidential Glass Ceiling Commission
(1995), the women's business advocacy group
Catalyst (1998), and the Society for Human
Everyone seems to have a list, from the Equal
Employment Opportunity Commission (1998)
Resources Management (2004). These lists are
Direct correspondenceto AlexandraKalev, RWJ
Scholars Program, University of California, 140
Warren Hall, MC7360, Berkeley, CA 94720
([email protected]).The authorsthank Ronald
Edwards and Bliss Cartwright of the Equal
EmploymentOpportunityCommission for sharing
their data and expertise;Nicole Esparzaand Leslie
Hinksonforhelp with datacollection;KevinDobbin,
JohnDonohue, LaurenEdelman,JoshuaGuetzkow,
Heather Haveman, Jerry A. Jacobs, Seema
Jayachandran,Lawrence Katz, JordanMatsudaira,
John Meyer,TrondPeterson,Daniel Schrage, Paul
Segal, Robin Stryker,Donald Tomaskovic-Devey,
BruceWestern,ChrisWinship,and four anonymous
reviewersfor suggestions; and Randi Ellingboe for
technical and editorial assistance. Supported by
National Science Foundation grant 0336642 and
Russell Sage Foundationgrant 87-02-03 and partiallysupportedby the RobertWoodJohnsonScholars
in HealthPolicy ResearchProgram.
AMERICAN
SOCIOLOGICAL
REVIEW,
2006, VOL.71 (August:589-617)
590
AMERICANSOCIOLOGICALREVIEW
loosely basedon academictheoriesthatpointto
causes of workplace inequality ranging from
unwitting bias (Lemm and Banaji 1999) to
dependence on networks for hiring and promotion (Reskin and McBrier 2000). Whereas
there has been a great deal of researchon the
sourcesof inequality,therehas been littleon the
efficacy of differentprogramsfor counteringit.
At best, "best practices"are best guesses. We
know a lot about the disease of workplace
inequality,but not much aboutthe cure.
We examine the effects of seven common
diversity programs-affirmative action plans,
diversity committees and taskforces,diversity
managers,diversity training,diversity evaluations for managers,networkingprograms,and
mentoringprograms-on the representationof
white men, white women, black women, and
black men in the managementranksof private
sector firms. Each of these programsmay well
increasediversity.To date, therehas been little
evidence one way or the other.This is surprising given the popularityand cost of the programs.Ourcontributionis to bringto bearrich
new data,to theoreticallydistinguishthreetypes
of diversityprograms,andto show thatorganizationalstructuresallocatingresponsibilityfor
changemaybe moreeffectivethanprogramstargeting eithermanagerialbias or the social isolation of disadvantagedgroups.
Previous empirical studies of antidiscriminationand diversityprogramshave been limited by data constraints. Economists first
comparedemployerswho are subject to affirmativeactionrequirementswith those who are
not (AshenfelterandHeckman1976;Heckman
and Wolpin 1976; Leonard1984). They lacked
data on employer programs.Sociologists and
economistsstudyingemployerprogramsexamine data at one or two points in time (but see
Baron,Mittman,andNewman 1991), analyzing
the effects of some programswithoutaccounting for others.These studiesindicatethatsome
programsmaybe effective,buttheirfindingsare
inconsistent (Baron et al. 1991; Edelman and
Petterson 1999; Holzer and Neumark 2000;
Konrad and Linnehan 1995; Leonard 1990;
Naff and Kellough 2003). Gender and racial
segregationhas declined remarkablysince the
1970s, when employers first adopted antidiscrimination programs (Jacobs 1989a; King
1992;Tomaskovic-Deveyet al. 2006), but there
is no hardevidence thatthese programsplayed
a role.
We obtainedthe federalestablishment-level
data that economists have used (i.e., the annual EEO-1 reportsthat privatesector establishments submit to the Equal Employment
OpportunityCommission [EEOC]). We then
surveyeda sampleof theseestablishmentson the
history of their personnel and diversity programsso thatwe could analyzeprogrameffects
on diversity.
A strengthof the EEO-1 reportsis that they
detail annual employment by race, ethnicity,
andgenderin all mediumand largeprivatesector workplaces.A limitationis that they cover
only nine broadjob categories,collapsing into
"management"all jobs above that of first-line
supervisor(Baronand Bielby 1985; Smithand
Welch 1984). We know frompreviousresearch
thatwomen andAfricanAmericansare crowded in the lowest ranksof management.Even as
women moved into managementin the 1970s
and 1980s, "womenmanagerscontinuedto trail
their male counterpartsin both earnings and
authority"(Jacobs 1992). Thus our analyses
indicatewhich diversityprogramshelp women
and African Americans move at least into the
bottomranksof managementand,importantly,
which do not. They cannottell us whetherany
of these practiceshelp women andminoritiesto
move into the executiveranks.
We find a clearpatternin the data.Structures
establishingresponsibility (affirmativeaction
plans, diversitycommittees,and diversitystaff
positions) are followed by significant increases in managerialdiversity.Programsthattarget
managerialstereotypingthrougheducationand
feedback(diversitytrainingand diversityevaluations)arenot followed by increasesin diversity. Programs that address social isolation
amongwomen andminorities(networkingand
mentoringprograms)are followed by modest
changes. The effects of these initiatives vary
across groups, with white women benefiting
most, followed by black women. Black men
benefit least. We also find that responsibility
structuresmake training,performanceevaluations, networking, and mentoring programs
more effective. Federal affirmative action
requirements,which typically lead to assignment of responsibilityfor compliance,also catalyze certainprograms.
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
These findings support an institutional theory of inequality remediation that builds on key
precepts of organizational sociology. As Weber
(1978 [1968]) argues, executives must appoint
specialists and give them authority to achieve
specialized goals. Thus, remedies targeting individual bias or network isolation may be less
effective than remedies that establish responsible parties. As neo-institutionalists (Meyer and
Rowan 1977) note, new programs decoupled
from everyday practice often have no impact.
Therefore, appointing a manager or committee
with responsibility for change is likely to be
more effective than annual diversity training,
periodic diversity evaluations, or decentralized
networking and mentoring programs. As structural theorists of organizational inequality claim
(Baron 1984), there is more to segregation than
rogue managers exercising bias. Thus, appointing special staff members and committees to
rethink hiring and promotion structures may be
more effective than training managers not to ask
their secretaries to make coffee, and not to
exclude minorities from football pools.
The argument that organizations should structure responsibility for reducing inequality may
seem commonsensical, but today's popular
diversity programs often focus on changing
individuals. In the academy generally and in
management studies particularly, methodological individualism now holds sway. Theorists
prescribe solutions that change incentives for,
and beliefs of, individuals with the idea that
most problems of management are problems
of motivation rather than structure. Thus the
most popular program that is not federally mandated is diversity training, designed to attack
bias. Managerial bias is also the target of diversity evaluations that offer feedback to managers. Networking and mentoring programs
may appear to operate at the collective level, but
they are designed to "fix" a lack of specific
human and social capital in individual workers.
Next, we describe the three categories of
diversity practices, link them to theories of
inequality, and summarize the (scant) evidence
about the effects of workplace antidiscrimination programs. Then we review the research on
the effects of the Civil Rights Act and presidential affirmative action edicts on employment-hitherto the main body of research on the
effectiveness of antidiscrimination measures.
After a discussion of data and methods, we
591
present the results from analyses of white men,
white women, black women, and black men in
management.
THREE APPROACHES TO INCREASING
MANAGERIAL DIVERSITY
Scholars often presume that practices designed
to attack known causes of inequality actually
will reduce it, as Reskin (2003) argues, making
a leap of faith between causes and remedies.
Thus, for example, although we know from
experimental psychology that unconscious bias
is endemic, and likely contributes to workplace
inequality, we can only hope that the prevailing
treatments-diversity
training and diversity
evaluations-diminish
inequality. Understanding the cause of malaria and understanding its treatment are two different things.
Whether a prescription for inequality is effective is an inherently empirical question. Current
prescriptions are not based in evidence.
Our goal is to take a first step toward developing an empirically based theory of remediation for organizational inequality. We sketch
three mechanisms for remediating workplace
inequality rooted in different social science literatures and discuss the popular human
resources (HR) measures thought to put these
theories to work. One mechanism, based in
arguments from Max Weber and organizational institutionalists, is the creation of specialized positions as the way to achieve new goals.
Another mechanism, based in theories of stereotyping and bias, involves training and feedback
as the way to eliminate managerial bias and its
offspring, inequality. A third mechanism, based
in theories of social networks, involves programs that target the isolation of women and
minorities as a way to improve their career
prospects.
ORGANIZATIONAL
CHANGE:STRUCTURES
OF
RESPONSIBILITY
We begin with a canonical insight from organizational theory. Organizational sociologists
and psychologists find that workers ignore
newly announced organizational goals and continue to pursue old goals with old routines. The
decoupling of formal goals and daily practice
may occur because individuals face information
overload, and thus stick to the familiar, or
592
AMERICANSOCIOLOGICALREVIEW
becausethe old ways of doing thingshavebeen
imbued with meaning and value over time
(Orton and Weick 1990; Selznick 1949).
Institutionalistsarguethat decoupling is common in programs responsive to regulatory
demands,such as civil rightsprograms(Dobbin
et al. 1988; Edelmanand Petterson1999; Scott
2001; Sutton and Dobbin 1996). Thus, for
instance,academicdepartments
haveabandoned
the old-boysystemof hiringin favorof openjob
advertisement,but departmentchairs still ask
theirpals for leads. Some arguethatmanagers
may simplynot perceiveit as in theirinterestto
promote gender and racial integrationof jobs
(Jacobs1989b).Decouplingis particularlylikely when there is no office or expertto monitor
progress, as Max Weber(1978 [1968]) hinted
when he arguedthatexecutives should appoint
specialists to pursue specialized goals.
If Weberand the institutionalistsarecorrect,
where diversity efforts are everyone'sresponsibilitybutno one'sprimaryresponsibility,they
aremorelikelyto be decoupled.In organizations
that do not assign responsibilityfor diversity
goals to a specific office, person, or group,
these goals may fall by the waysideas line managersjuggle competing demandsto meet production quotas, financial targets, and the like
(Edelman 1990; Meyer and Rowan 1977).
Scholars(Reskin 2003; Sturm2001) and consultants(Winterle 1992) alike advise ongoing
coordination and monitoring of diversity
progress by dedicated staff members or task
forces. Threecommon approachescan be used
to establishresponsibilityfor diversity,as discussed in the following sections.
RESPONSIBILITYAND AFFIRMATIVEACTION
PLANS.
Assign responsibilityfor setting goals,
devising means, and evaluatingprogress;this
was Weber'sadvice to bureaucrats.The agency
LyndonJohnsonset up in 1965 to monitoraffirmativeactionamongfederalcontractorsencouraged this approach. In 1971, the Office of
Federal ContractCompliance (OFCC, which
later gained a P for "programs"to become
OFCCP)orderedcontractorsto write affirmative action plans in which they annuallyevaluate their own workforces,specify goals for the
fair representationof women and minorities
based on labor market analyses, and sketch
timetables for achievement of these goals
(Shaeffer 1973:66).
The order also specifies that firms should
assign responsibilityto a staff member:"He or
she must have the authority,resources,support
of and access to top managementto ensurethe
effective implementation of the affirmative
action program"(U.S. Department of Labor
2005). By collecting andreviewinglocal information annually,the affirmativeaction officer
can track "underutilization"of women and
minoritiesand keep managersinformedabout
their departments' progress (Linnehan and
Konrad1999:410; Reskin 2003:13) or initiate
"constructivedialogue"about making further
progress(Sturm2001).
The few studiesthatexamineeffects of affirmative action plans are inconclusive. Baron et
al. (1991), studying annual data from 89
California state agencies between 1975 and
1981, foundthat,all else being equal, agencies
with affirmativeaction programsmade significantly slower progress in gender desegregation of jobs. Yet those agencies were more
integratedoriginally,so it may be that preexisting affirmativeaction programshad left little roomfor improvement(see also Edelmanand
Petterson 1999:126; Leonard 1990:65). In a
study of 3,091 federal contractorswith affirmative actionplans JonathanLeonard(1985b)
shows that the goals employers set for hiring
white women,blackwomen, andblackmen did
have positive effects, althoughthe goals were
wildly optimistic. Goals apparentlydo not act
as quotas because virtually no employer ever
achieves its writtengoals.
Federalcontractorsarerequiredto writeaffirmative action plans, but contractorstatusdoes
not correspondperfectlywith the presenceof a
plan. Many contractorsfail to write plans or to
updatethem (Bureauof NationalAffairs 1986;
Leonard 1990:55). Up to one fourth of firms
with affirmativeactionplansarenot contractors.
They createplans to bid for contractsor to set
diversity goals (Bureau of National Affairs
1986;Reskin 1998). In oursample,7 percentof
contractorsneverhad a plan, and 20 percentof
firms thathadneverhad a contractwroteplans.
OVERSIGHTVIA STAFFPOSITIONSAND DEPART-
MENTS.Following the classic bureaucratic dic-
tum (Weber1978 [1968]), some organizations
appointfull-timestaffmembersor createdepartmentsto monitordiversityinsteadof leavingthe
task to line managersor assigning it to staffers
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
with otherresponsibilities.As a newly appointed diversity managerin a high tech company
explainedto us in 2001: "Asthe organizationhas
startedto grow,they realizedtheyneededsomeone in there to really pay attentionto affirmative action and compliance and ... efforts on
diversity.... So the position was createdat the
beginning of this year."
Big militarycontractorswere the first to create special positions, in the wake of Kennedy's
initialaffirmativeactionorderin 1961.Edelman
and Petterson(1999) show that equal opportunity departmentsdo not increase gender and
racial diversity on their own, but that they do
expanddiversityrecruitmentprograms,which
in turnimprovediversity.We includea measure
for recruitmentprogramsto isolate the effects
of diversitystaff positions.
OVERSIGHTAND ADVOCACYVIA COMMITTEES.
From the late 1980s, experts have advised
employersto appointdiversitycommitteesand
task forces comprising people from different
departments,professional backgrounds, and
managerial levels. Committees typically are
charged with overseeing diversity initiatives,
brainstormingto identify remedies, and monitoringprogress.The diversitytask force at the
accounting and consulting giant Deloitte &
Touche, for instance, createda series of ongoing groupsresponsiblefor analyzingthe gender
gap, recommendingremedialsteps, and establishingsystemsformonitoringresultsandensuring accountability(Sturm2001:492).
These three strategies share a focus on
responsibility.An organizationwith any one of
these has assignedresponsibilityfor progressto
a person or group-an affirmativeaction officer, a diversity manager or department,or a
committee or task force. Thatperson or group
monitorsprogressregularly.Affirmativeaction
officers also write explicit annual goals for
progress,as do some staffersand committees.
BEHAVIORAL
CHANGE:
REDUCING
BIAS
THROUGH
EDUCATION
ANDFEEDBACK
Social psychologists trace inequality to bias
amongmanagers.Stereotypingis a naturalcognitive mechanism. It is inevitable given our
innocenttendencyto makeassociationsbetween
categories and concepts (Gorman 2005;
Heilman 1995; Lemm and Banaji 1999). The
593
implicit associations we make between race,
gender,ethnicity,and social roles can have the
effect of reproducing existing patterns of
inequality (Jost, Banaji, and Nosek 2004).
Managersmay unwittingly select women for
jobs traditionally dominated by women and
men forjobs dominatedby men, with the effect
of preserving between-group differences.
Moreover in-group preference is widespread
(TajfelandTurner1979) andmay likewise contaminate managerial judgment (Baron and
Pfeffer 1994; Reskin 2000). Rosabeth Moss
Kanter(1977) sketchesthe earlyresearchon ingroup preference to support her theory of
homosocial reproduction-white men promoting their clones. Kanterargues that managers
preferto hire their own for reasonsof communication and trust.
Twocorporateinitiativesarethoughtto counter stereotyping and in-group preference.
Diversitytrainingis thoughtto makemanagers
awareof how bias affectstheiractionsandthose
of subordinates. Diversity evaluations are
thought to provide managers with feedback
showingthe effects of theirdecisions on diversity.
EDUCATIONVIA DIVERSITYTRAINING.Social
psychological researchshows that giving people informationaboutout-groupmembersand
aboutstereotypingmayreducebias (Fiske 1998;
Nelson, Acker, and Melvin 1996). Diversity
trainingprovidesmanagerswith such information. It can be tracedto the equal opportunity
"sensitivity"trainingprogramsthata handfulof
major corporations put together in the mid1970s in responseto the first equal opportunity consent decrees and court orders (Shaeffer
1973). By the late 1980s, quite a few corporate
trainersandpsychologistshad developedtraining modules designedto familiarizeemployees
with antidiscriminationlaw, to suggest behavioral changes that could address bias, and to
increase culturalawarenessand cross-cultural
communication(Bendick, Egan, and Lofhjelm
1998).
Employersusually offer trainingeitherto all
managersor to all employees. We look at the
effects of trainingoffered at least to all managers.Some studiesof diversitytrainingsuggest
that it may activate rather than reduce bias
(Kidder et al. 2004; Rynes and Rosen 1995;
Sidanius,Devereux,andPratto2001). Research
594
AMERICANSOCIOLOGICALREVIEW
on diversity training programs has seldom
exploredtheireffectson workforcecomposition,
but one study of federal agencies (Naff and
Kellough 2003) did show that a broaddiversity programhad a negative effect on the promotion of minorities(Krawiec2003:514).
FEEDBACKVIA PERFORMANCEEVALUATIONS.
Feedbackis thoughtto reducebias by directing
managerial attention and motivation (Reskin
2003:325). Laboratoryexperimentsshow that
when subjects know that their decisions will
be reviewedby experimenters,they show lower
levels of bias in assigning jobs (Salancik and
Pfeffer 1978; Tetlock 1985). Evaluatingmanagers on their diversity performance creates
oversight and provides feedback. As early as
1973, the HarvardBusiness Reviewnoted that
"as one criterionof a line manager'sperformance appraisal,some companieshave included
his success in effectively implementingequal
opportunity programs" (Fretz and Hayman
1973:137). By the mid-1980s, a study of nine
exemplaryfirms found that managersin each
firm received regular equal opportunityperformanceevaluations(Vernon-Gerstenfeld
and
Burke1985:59-60). To ourknowledge,no studies assess the effects of diversityevaluations.
TREATINGSOCIALISOLATION:NETWORKING
AND MENTORING
MarkGranovetter(1974) broughtinsightsabout
social networks,pioneeredby both sociologists
and psychologists, to the study of how people
find jobs. Students of inequality have since
speculated that differential network contacts
and differentialresourcesaccruingfrom these
contacts may explain part of the continuing
inequality between whites and blacks, and
betweenmen andwomen(Blair-Loy2001; Burt
1998; Ibarra 1992, 1995; McGuire 2000;
Petersen, Saporta, and Seidelm 1998). White
men are more likely than others to find good
jobs through network ties because their networks are composed of other white men who
dominatethe uppertiers of firms (Burt 1998;
Reskin and McBrier 2000, but see Fernandez
and Fernandez-Mateo 2006; Mouw 2003).
Social networksalso encouragetrust,support,
andinformalcoaching(BaronandPfeffer1994;
Castilla 2005; Kanter 1977). Networking and
mentoringprogramsdesigned specifically for
women and minorities are thought to provide
usefulcontactsandinformation(Thomas2001).
Both types of programswere pioneeredin the
1970s and then revived in the 1990s as partof
diversitymanagementefforts(Wernick1994:25;
Winterle 1992:21).
NETWORKINGPROGRAMS.Diversitynetworking programsfor women andminoritiesvary in
structure.Some takethe formof regularbrownbag lunchmeetings,whereasothersincludelavish national conferences (Crow 2003). These
programsmay be initiatedby employees or by
HR managers.They provide a place for members to meet and share informationand career
advice. Some networks also advocate policy
changes,suchas those involvingfamilypolicies
and domestic-partner benefits (Briscoe and
Safford2005). Althoughnetworkingmay occur
without any organizationalimpetus,we examine formal networkingprogramsthat employers supportthroughreleasetime forparticipants,
meeting space, funding,newsletters,and email
lists.
MENTORING
PROGRAMS.
In 1978, the Harvard
Business Review published an article titled
"EveryoneWho Makes It Has a Mentor"that
made mentors a must-have for aspiring management trainees (Lunding, Clements, and
Perkins1979;see also Roche 1979). Proponents
of formal mentoringprogramsarguethat they
can level the playing field, giving women and
minoritiesthe kinds of relationshipsthatwhite
men get through the old-boy network.
Mentoringprogramsmatch aspiringmanagers
with senior mentors,with the two meeting for
career counseling and informal advice.
Empiricalstudies,such as BurkeandMcKeen's
(1997) survey of universitygraduates,suggest
a relationshipbetween mentoring and career
success among women, but do not rule out the
possibility that ambitious women seek mentors. One study of randommentorassignment
within a single firm found that, in general,
mentees have improved social networks and
tacticalknowledge,whichmayhelptheircareers
(Moore2001). Othershavefoundthatcross-race
mentoring relationships often fail (Thomas
2001), and that same-sex mentoringdoes not
have a positive effect on job placementin aca-
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
demic departments of economics (Neumark
and Gardecki1996).
ADVERSE
EFFECTS
OFDIVERSITY
PRACTICES
Some argue that affirmativeaction and diversity programs can backfire (Bond and Pyle
1988; Linnehanand Konrad1999). First,executives may believe that women and minorities
benefit from reverse discriminationand thus
may not deserve their positions (Heilman,
Block, and Stathatos1997;but see Taylor1995).
Second,because of the elusive natureof cognitive bias, "conscious attemptsat thoughtregulation"-such as diversitytraininganddiversity
evaluations-"may even backfire, leading to
exaggeratedstereotypingunder conditions of
diminished capacity, or when self-regulation
efforts are relaxed" (Nelson et al. 1996:31).
Indeed,managementconsultantsandresearchers
find mixed reactionsto diversitymanagement
among white males, who report that they are
"tiredof being made to feel guilty in every discussion of diversity... of being cast as oppressors" (Hemphill and Haines 1997). Third,
coworkersand executives may have negative
reactions when they perceive minorities "as
attemptingto obtain power by individual and
collectivemeans"(Ragins 1995:106),andexecutives may fear that networking will lead to
union organizing(Bendick et al. 1998; Carter
2003; Friedman and Craig 2004; Miller
1994:443; Society for Human Resources
Management2004). Finally,some studies find
thatraciallydiverseworkgroupscommunicate
less effectivelyandareless coherent(Baughand
Graen 1997; Townsendand Scott 2001; Vallas
2003; Williams and O'Reilly 1998). Taken
together,this research suggests that diversity
programsmay inhibit management diversity,
particularlyfor blacks.
THE CIVILRIGHTS ACT, AFFIRMATIVE
ACTION EDICTS,AND DIVERSITY
PRACTICES
Although there is little researchon the effects
of corporatediversityprograms,the Civil Rights
Act and presidentialaffirmativeaction orders
havebeen shownto increasediversity.The Civil
RightsAct coversvirtuallyall employers,making researchon its effectsdifficult(Donohueand
Heckman 1991). The effects of presidential
595
affirmativeaction orders can be examined by
comparingfederal contractorssubjectto these
orders with noncontractors.Six studies using
EEOCdatafor periods of 4 to 6 years between
1966 and 1980 show that black employment
grew more quickly among contractors
(AshenfelterandHeckman1976;Goldsteinand
Smith 1976; Heckman and Payner 1989;
HeckmanandWolpin1976).Affirmativeaction
hadnegligibleeffectson whitewomen(Leonard
1989:65). Contractoreffects on blacks, especially black women, declined from the early
1980s (Leonard 1990:58), coincidentwith the
Reaganadministration's
policy of deregulation.
These studies do not look at whether federal
contractors increased black employment by
adoptingantidiscriminationpractices.The two
exceptions are a study by Leonard (1985b)
showing that employerswho set high recruitment goals see more change and a study by
Holzer and Neumark (2000) showing that
employers subject to affirmative action law
expandrecruitmenteffortsandhiremoreapplicants from disadvantagedgroups.We examine
the effect of affirmative action orders and
explorethe possibilitythatbeing subjectto such
orders(bybeing a federalcontractor)rendersthe
seven diversityprogramsmore effective.
In summary,we expect the differentsorts of
diversityprogramsto varyin efficacy.If assigning organizationalresponsibilityis more effective than targetingthe behaviorof individuals,
then affirmative action plans, diversity committees,andfull-timediversitystaffwill be followed by broader increases in diversity than
will eitherdiversitytrainingand diversityevaluations,or networkingandmentoringprograms.
By the same logic, the latterfourprogramsmay
be more effective when implementedin organizations with responsibilitystructures.Finally,
we examinewhetheraffirmativeactionoversight
rendersprogramsmore effective.
ALTERNATIVESOURCES OF CHANGE
IN THE MANAGERIALWORKFORCE
We includein the analysesotherfactorsthought
to affect management diversity. We cannot
include factorsthatdo not vary with time, such
as industryor location,becauseourfixed-effects
models account for such stabletraits.
596
AMERICANSOCIOLOGICALREVIEW
LEGALENVIRONMENT
Legal enforcement, through OFCCP compliance reviews, lawsuits, and EEOC charges,
should increase employers'hiring and promotion of women and minorities (Baron et al.
1991:1386; Donohue and Siegelman 1991;
Kalev andDobbin forthcoming;Leonard1984;
Skaggs 2001).
ORGANIZATIONAL
STRUCTURES
Organizationalsize andthe availabilityof managerialjobs createnew opportunities(Baronet
al. 1991), but also more competition.Konrad
and Linnehan (1995) and Leonard(1990:52)
find thatincreaseddemandfor managersfavors
white women, but not African Americans.
Unionizationtends to preserve segregationby
favoringold timersthroughseniorityprovisions
(Blau and Beller 1992; Milkman 1985; but see
Kelly 2003; Leonard1985a). Formalizationof
personnel systems can reduce favoritism
(Dobbinet al. 1993;ReskinandMcBrier2000),
althoughit also can create separatecareertrajectoriesfordifferentgroups(BaldiandMcBrier
1997; Baron and Bielby 1985; Elvira and
Zatzick 2002). Legal counsel may sensitize
employersto diversityin promotiondecisions,
and recruitmentsystems targetingwomen and
minoritiescan increasediversity(Edelmanand
Petterson 1999; Holzer and Neumark 2000).
Finally,work/familypolicies mayremoveobstacles to the promotion of women (Williams
2000).
Zatzick 2002; Kletzer 1998). Finally,growing
industriescan offer more attractivejobs, and
both women and minorities have historically
been relegatedto less attractivesectors(Reskin
and Roos 1990:298).
DATA AND METHODS
We conducted a fixed-effects analysis of longitudinaldataon the workforcecompositionof
708 establishmentsto assess changes in managerialcompositionafterthe adoptionof each of
seven diversity practices. The data cover the
period1971-2002. Fixed-effectmodelsaccount,
implicitly,for organizations'unobservedcharacteristicsthat do not vary over time and that
may affect diversity.
EEOCDATA
The Civil Rights Act of 1964, as amended,
requiresprivateemployerswith more than 100
employees and government contractors with
more than 50 employees and contractsworth
$50,000 to file annual EEO-1 reports.These
reportsdetail the race, ethnicity,and genderof
employees in nine broad occupational categories. There are no better data on workforce
composition(fora methodologicaldiscussionon
using EEO-1reports,see Robinsonet al. 2005).
We obtainedthe data from the EEOC through
an Intergovernmental
PersonnelAct (IPA)agreement.
Some arguethatemployersreclassifiedjobs
in the 1970s, moving women and minorities
TOPMANAGEMENT
COMPOSITION
into managementcategories to improve their
The diversityof the top managementteammay
federal reports (Smith and Welch 1984).
affect managerial hires through homosocial
Leonard(1990:53) notes that "purereclassifireproductionor social closure (Kanter 1977;
cation would cause black losses in the lower
Tomaskovic-Devey1993).
occupations[in the EEO data],which is generally not observed."Jacobs (1992:298) shows a
LABORMARKET
ANDECONOMIC
ENVIRONMENT declining gender earningsgap consistent with
realprogress,notingthat"thepredominanttrend
Firms can more easily increase managerial
has
been towardreal,if slow progressinto mandiversitywhen internalandexternallaborpools
agement
on the partof women."In our sample,
are diverse (Cohen, Broschak, and Haveman
few
firms
show suddenincreasesfor women or
1998; Shenhavand Haberfeld 1992). Demand
blacks
in
management,
but we checked results
for workersfromunderrepresented
groupsmay
for robustnessby eliminatingthese cases, and
be higher in industrieswith more federal conthe results did not change. We also eliminated
tractors.In hardeconomictimes,blackmen, and
to a lesser extent women, are more vulnerable establishment-yearspells frombefore 1990, as
than white men to being laid off (Elvira and
discussed later,and the findings held up.
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
ORGANIZATIONAL
SURVEYDATA
We drew a random sample of establishments
fromthe EEO-1 databasefor our organizational survey. For that sample, we constructed a
dataset comprising all EEO-1 reports for the
years 1971-2002, interpolatingfor the missing
years of 1974, 1976, and 1977. Establishments
enter the datasetwhen they begin filing EEO1 reports.To ensurethatwe wouldbe ableto follow establishmentsover time, we chose half of
the sample from establishmentsthat had been
in the datasetsince 1980andhalf fromthosethat
had been in the dataset since 1992. We also
stratifiedby size, selecting 35 percentof establishments with fewer than 500 employees in
1999, and by industryto representthe manufacturing,service,andtradesectors.We sampled
from food, chemicals, computer equipment,
transportation
equipment,wholesaletrade,retail
trade,insurance,business services, and health
services. Corporatediversitycan be influenced
by acquisitions,spin-offs,andplantclosings, so
we sampledestablishments,selecting no more
than one per parentfirm.
We conducted a longitudinal survey of
employment practices at each establishment
coveringthe years 1971-2002, in collaboration
with the PrincetonSurveyResearchCenter.We
drewon the experiencesof otherswho hadconducted organizationalsurveys of employment
practices (particularlyKalleberg et al. 1996;
Kelly 2000; Osterman 1994, 2000). We completed 833 interviews,for a responserateof 67
percent, which compares favorably with the
rates of those other organizationalsurveys. In
preparation,we conducted41 in-personinterviews with HR managersfrom randomlysampled organizationsin fourdifferentregions,and
20 pilot phone interviews. Data from those
interviews are not included in the analyses
reportedin this discussion.
We began by writing to the HR directorat
each establishment.We askedfor permissionto
conduct an interview and for the name of the
person who could best answerquestionsabout
the establishment'shistoryof HR practices.The
typicalintervieweewas an HR managerwith 11
yearsof tenure.We scheduledphoneinterviews
at the convenience of the interviewees, and
explained in advance the nature of the information needed. We asked whether the establishmenthadeverused eachpersonnelprogram,
when it was adopted,and whetherand when it
597
hadbeen discontinued.Programdiscontinuation
was rare.When a respondentcould not answer
a question, we sent a copy of that question by
email or fax, askedthatshe consultrecordsand
colleagues,andcalled backto fill in the blanks.
Duringour in-personpilot interviews, respondentsroutinelypulled out manualswith copies
of policies and lists of adoption and revision
dates. Nonetheless, because responses about
events long past may be inaccurate,we replicated the analyses using only establishmentyear spells for 1990 to 2002, as discussed later.
We matched survey data for each establishment with annual EEO-1 records, creating a
datasetwith annualestablishment-yearspells.
After excluding 10 cases that had EEO-1 data
availablefor fewer than 5 years, 13 cases with
excessive numbersof missing values for EEO1 or surveydata,and 102 cases thatwere missing the adoption date for at least one key
program,our final datasetincluded 708 cases
and 16,265 establishment-year cells, with a
medianof 25 years of dataper establishment,a
minimum of 5 years, and a maximum of 32
years.We collected dataon national,state, and
industryemploymentfromthe Bureauof Labor
Statistics.
Because of our stratified sampling design
and the response pattern,we were concerned
thatrespondentsmight not representthe populationof establishmentsthatfile EEO-1reports
in the sampled industries. We constructed
weightsbased on the inverseprobabilitythatan
establishmentfrom each stratum(industryby
size and by time in the EEO-1 dataset)would
completethe survey.We replicatedall reported
analysesusingweights,andthe resultsremained
intact.We reportunweightedresults in the following discussion(WinshipandRadbill 1994).
We also were concerned that employers who
refusedto participatemight systematicallydiffer, on factors affecting diversity,from those
who participated.We included in the models
predictedvalues froma logistic regressionestimating the probabilityof response (Heckman
1979). This did not change our results.
Covariatesin that model were industry,establishment status (headquarters,subunit, standalone status),size, contractorstatus,managerial
diversity,andcontactperson'sposition.The last
variablewas obtainedin the initial contact,the
others from the EEO-1 data.
598
AMERICANSOCIOLOGICALREVIEW
DEPENDENTVARIABLES
The dependentvariablesare the log odds that
managersare white men, white women, black
women, and black men . For each group, odds
are calculated as the proportionof managers
from that group divided by the proportionnot
from that group (proportion/(l- proportion)).
Figure 1 presentsthe trends,in percents,in our
sample. Between 1971 and 2002, management
jobs held by white men decline from 81 to 61
percent in the average establishment.
Managementjobs held by white women rise
from 16 to 26 percent, whereas those held by
black women rise from 0.4 to 2 percent, and
those held by black men rise from 1 to 3.1 percent. There also is a significant rise in the representationof othergroups,notablyHispanics,
duringthisperiod,whichis why the percentages
do not sum up to 100 percent.
Black women and men showed dramatic
changes in their proportions in management
relativeto the baseline,quadruplingandtripling,
respectively,but saw small changes in percentage points. Because the absolute changes for
blacks are relatively small we log the dependent variables.We use log odds, ratherthan log
proportion,because the distributionis close to
normal (Fox 1997:78).1In a sensitivity analysis, log proportionperformed very similarly.
The dependentvariableis measuredannually,
one year after the independent variables.
Changingthe lag to 2, 3, or 4 yearsdoes not alter
the findings. Our sample is designed to investigatethe effects of diversityprogramson workforce composition in private sector
establishments large enough to file EEO-1
reports.We do not claimto describethe nation's
managerialworkforce.Nationallyrepresentative
samples such as the CurrentPopulationSurvey
include the public and nonprofit sectors, in
which the gains of women and minoritieshave
1 Becauselog-odds(logit)is undefinedat values
of 0 and 1, we substituted
0 with 1/2Nj,and1 with
1-1/2Nj,whereNj is the numberof managersin
establishmentj (HanushekandJackson1977;Reskin
andMcBrier2000).Theresultswererobustto differentsubstitutions
for0. Wechosetheonethatkept
thedistribution
unimodalandclosestto normal.To
ensurethatthe substitution
doesnotdrivethe findings,we includea binaryvariablefornogroupmembersin management.
been larger.Furthermore,
nationalfiguresreflect
the change in women'srepresentationin managementassociatedwith service sector growth
(e.g. Jacobs 1992), whereas our data track a
relativelystable set of firms.
AFFIRMATIVE
ACTIONPLANSANDDIVERSITY
PRACTICES
Figure2 showstheprevalenceof all sevendiversity programsamong the 708 employers analyzed later.By 2002, affirmativeaction plans
were used in 63 percent of the workplaceswe
study,followedby trainingin 39 percent,diversity committeesin 19 percent,networkingprograms(forwomenandminorities)in 19 percent,
diversityevaluationsformanagersin 19 percent,
diversitystaffin 11 percent,andmentoringprograms(forwomenandminorities)in 11 percent.
The bivariate correlations and joint frequencies of the seven programsare not shown here
(see Online Supplement,ASRWeb site: http://
www2.asanet.org/joumals/asr/2006/toc052.html).
In the analysesreportedin the following discussion,we use binaryvariablesto representthe
presenceof the sevendiversityprograms.Forsix
programs,we asked whetherthe organization
had ever had the program,when it was first
adopted,andwhen (if ever)it was discontinued.
Forthe seventhpractice,diversitytraining,we
asked when it was first and last offered. If an
employerhadgone for 3 yearswithouttraining,
we treatedthe programas defunct.We collected additionalinformationaboutdiversitytraining becauseourin-personinterviewssuggested
that it varied across organizationsmore than
the other programs,but we found significant
similaritiesin trainingprograms.In 70 percent
of the establishmentswith training for managers, trainingwas mandatory.Includedin 80
percentof the trainingprogramswas a discussion on the legal aspectsof diversity,and98 percent were conducted with live facilitators,as
opposed to being offered exclusively via the
Web or video. Although some organizations
offered trainingnot only to managers,but also
to all employees, we reporteffects of training
for managersbecause managersmade promotion decisions. Trainingfor all employees had
nearlyidenticaleffects in the models.
Because the measures are binary, coded 1
for all the yearsthe programis in place,program
effects are estimated for the entire period of
CORPORATEAFFIRMATIVEACTIONAND DIVERSITYPOLICIES
599
90%
80%
70%
60%
50%
managers
of
40%
percent
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Year
S----
White Men -0---
White Women -4-
Black Men - - - - Black Women
Figure 1. Percent of Managers: White Men and Women and Black Men and Women, 1971-2002
Note: Based on EEO-1 reports 1971-2002 sampled for Princeton University Human Resources Survey 2002.
Varying N. Maximum N = 708; EEO = equal employment opportunity.
40%
Workplace
of 30%
20%
percent
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Year
--AA Plan
--A-- Diversity Committee
-0-- Diversity Training
- - -Mentoring for Women/Minorities
--4-
FullTimeEO/AAStaff
DiversityEffortsin Mgrs'Evaluations
-)--
Networking for Women/Minorities
Figure 2. Percentof Private-SectorWorkplaceswith Affirmative Action Plans and Diversity Programs, 1971-2002
Note: Based on Princeton University Human Resources Survey, 2002. Varying N. Maximum N = 708.
600
AMERICANSOCIOLOGICALREVIEW
the program'sexistence(notmerelyfor the year
after initiation).
For six of the programs,between 2 and 4
percent of the respondentswho reported the
program'sadoptioncould not tell us the exact
year.Forthe seventhpractice,affirmativeaction
plan, the figure was 8 percent.We eliminated
cases with missing data on any of these variables.The resultswere virtuallyidenticalwhen
we imputedmissing datafor variablesof interest and retained these cases in the analysis.
Missing adoption dates for control variables
were imputed using ordinary least squares
(OLS) regression, with industry,age of establishment, and type of establishmentas covariates. Omittingcases with imputeddatadid not
substantiallyalterthe findings.
CONTROL
VARIABLES
All measures included in the analyses vary
annually.Table 1 presentsdefinitions and data
sources for key variablesas well as means and
standarddeviations(basedon all organizational spells). Descriptivestatisticsfor the entirelist
of control variables are not shown here (see
Online Supplement,ASR Web site). Because
the fixed-effects method estimates variation
withinthe organization,it captureschangeover
time. For example, in the models, the variable
organizational size captures the effect of a
change in size on change in managerialdiversity.These models effectively ignore measures
thatdo not change, such as industry,but crosscase variationin those measuresis capturedby
the fixed effects.
LEGALENVIRONMENT.
We include a binary
variablebased on the EEO-1 reportsindicating
whetherthe establishmentis a federalcontractor subject to affirmative action regulation.
Legal enforcementis measuredusing threesurvey variables that capturethe establishment's
experience with Title VII lawsuits, EEOC
charges, and affirmative action compliance
reviews. Each is coded 1 from the year of the
firm'sfirst enforcementexperience.Morethan
one thirdof establishment-yearspells had previously faced a lawsuit; more than one third
had faced an EEOCcharge;and nearly 15 percent had faced a compliancereview (only contractorsare subjectto compliancereviews).
ORGANIZATIONAL STRUCTURES. Organizationalsize andavailabilityof managerialjobs
are measured using EEO-1 data on the total
numberof employees in the establishmentand
the number of managerial employees.
Unionization is coded 1 when the establishment has at least one contract. Substituting
with a measure of core job unionization does
not alterthe results.FormalHR policies involve
a count of hiring, promotion, and discharge
guidelines; job descriptions; promotion ladders;performanceevaluations;pay grade system: and internaljob posting. Legal counsel is
measuredwith a binary variable for the presence of an in-house attorney.Targetedrecruitment policy is a binary measure of special
diversityrecruitmentefforts.Work-familysupport counts paid maternityleave, paid paternity leave, flextimepolicies, andtop management
supportfor work-family programsas assessed
by our respondents.
TOP MANAGEMENT
COMPOSITION.
Top management team diversity is measured with the
percentage of the top 10 positions held by
women and/or African Americans, based on
survey data.We asked aboutthe percentageat
10-year intervals and interpolatedvalues for
the interveningyears.
LABORMARKETAND ECONOMIC
ENVIRONMENT.
The diversity of the establishment's internal
laborpool is measuredwith two variablesbased
on the EEO-1 reports:the percent of the focal
groupin nonmanagerialjobs andthe percentin
the corejob. To determinethe EEO-1 category
that held the core job, we asked respondents
about the single biggest job in the organization. We include a variablecoded 1 when there
are no membersof the focal group in management. Diversityof the establishment'sexternal
laborpool is capturedby two sets of variables
on industry and state labor forces from the
CurrentPopulationSurvey. Industryemploymentvariablesarelogged.Weuse the industry's
percent of governmentcontractors(based on
EEO-1 data)to measuredemandfor underrepresentedworkersin affirmativeaction sectors.
Economic conditions are measured with the
yearly state unemploymentrate, and industry
size is measured as total annual industry
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
6ol
Data EEO-1
shown
EEO-1Survey
Survey
Survey
Survey
Survey
EEO-1
EEO-1
Survey
Survey
Survey
EEO-1
Survey
Survey
EEO-1
EEO-1
Survey
Survey
Survey
Survey
Survey
Survey
Survey
not
opportunity;
variables
of
Type
Count
Count
Count
Binary
Binary
Binary
Binary
Binary
Binary
BinaryBinary
Binary
Binary
Binary
Binary
Binary
list
Continuous
Continuous
Continuous
Continuous
Continuous
Continuous
Continuous
Continuous
employment
10010066.7
100
Maximum
1 1 1 1 1 1 1
1 1 1 1
.789 1
9 1 1 4
100100
12,866
detailed
a equal
=
for
2
EEO
Table
to
note
See
0 0 0 0
0 0 0 0 0 0 0
0 0 0 0
10 0 0 0 0 0
.002
0 0
here.
Minimum
shown
not
but
Deviation
4.25.9
23.6
21.2
.494
.206
.222
.244
.303
.244
.179 .498
.356
.474
.464 .090 .436 .448
.978
.363
analyses
2.516
10.239
23.575
827
the
in
Standard
http://www2.asane
included
site:
are
Web
Composition
1.4
22.2 2.4
Mean 70.0
Workforce
.156
.912 3.471
.045
.052
.064
.102
.064
.033 .455
.149
.341
.314 .124 .254 .277
.422
4.917
16.445 ASR
702
variables
Supplement,
environment
Managerial
of
contract)
Analysis
in
minorities
Measures
and
Online
on
economic
(percent) and
variables
men
women
women
men
staff
managers (government
women minorities
women
market
of
Diversity
establishment for
areare control
status
white
white
black
black plan
in
and
of
Variables(percent)
Labor
Composition
lawsuits size
areareareare
who
who list
accommodations
Structures
review
action
action
programs
policies
resources.
programs
who
who
who
who
committee
evaluations
training
ActionEEO/diversity
attorney
16,265.
Selected Variables
managers
recruitment
HR
entire
charges
agreement
=
time
managers
managers
1.
Environment
N (seehuman
Management =
Special
Top
Top
Establishment
Formal
In-house
Work-family
Compliance
Discrimination
EEOCPercent
Union
Diversity
Diversity
Mentoring
Affirmative
Managers
Managers
Affirmative
FullDiversity
Managers
Managers
Networking
HR
Top
here
Legal
Organizational
Note:
Affirmative
Table Outcome
Used
602
AMERICANSOCIOLOGICALREVIEW
employment,both fromthe CurrentPopulation
Survey.
METHODS
Weuse pooled cross-sectionaltime-seriesmodels, with fixed effectsforbothestablishmentand
year (Hicks 1994; Hsiao 1986). We use fixed
effects for establishmentsto accountforunmeasured,time-invariantcharacteristicsthatmight
affect outcome variables(for recent empirical
examples of these methods appliedto individuals, see Budig and England 2001; Western
2002). This specification, achieved by subtracting the values of each observation from
the establishment mean (Hsiao 1986:31),
strengthens our causal inferences about the
effects of affirmativeaction plans and diversity practices by ruling out the possibility that
organizationsthat adoptedthose practiceshad
stableunobservedpreferencesfor diversity.To
captureenvironmentalchanges, such as legal
and culturalshifts, we use a binaryvariablefor
each year, omitting 1971. The large numberof
parametersinvolvedin estimatingfixed-effects
models rendersthem less efficient than other
estimators.However,we prefer these to alternative models because they provide the most
stringent tests of our hypotheses. The establishment and year fixed effects also offer an
efficient means of dealing with nonconstant
varianceof the errors(heteroskedasticity)
stemming from the cross-sectional and temporal
aspects of the pooled data.
Because our dependentvariablesare measured as parts of the same whole (the whole
being managementjobs), we expect theirerror
terms to be correlated.Ordinaryleast squares
wouldthusproduceunbiasedandconsistent,but
inefficient, estimators.We use seeminglyunrelated regression, which takes into account
covariance between the errors and produces
unbiased, efficient estimators (Felmlee and
Hargens 1988; Greene 1997; Zellner 1962).
Simultaneousestimationalso allows us to comparethe effect of each diversitypracticeacross
groupswith formalchi-squaretests (Kalleberg
and Mastekaasa2001; Zellner 1962).
FINDINGS
The analysis shows substantialvariationin the
effectiveness of diversity programs. Some
increasemanagerialdiversityacrossthe board,
whereas others have meager effects, or positive effects for some groupsandnegativeeffects
for others.Themost effectivepracticesarethose
thatestablishorganizational
responsibility:affirmative action plans, diversity staff, and diversity task forces. Attempts to reduce social
isolationamongwomenandAfricanAmericans
through networkingand mentoring programs
areless promising.Leasteffectiveareprograms
for taming managerialbias througheducation
and feedback.
DIVERSITY
PROGRAMS
AT WORK
In Table 2, we report models of managerial
diversity. (Selected control variables are presented;the remainingcoefficients can be seen
on the OnlineSupplement,ASRWebsite). Each
dependentvariableis the (natural)log odds of
managersbeing froma certaingroup.To transformthe coefficient[pfromrepresentingchange
in log odds to representingpercentagechange
in odds, it should be exponentiated:[exp([3)1]*100. Once exponentiated in this way the
coefficient representsthe average percentage
changein the oddsthatmanagersarefroma certaingroup,associatedwith a changein the independentvariable.Inthe discussionbelow we use
'odds for [group]'as a shorthand.We also provide an illustrativesummaryof the results in
proportionterms.
The R2 figures for these fixed-effects models represent the percentage of the variance
explained by the predictorswhen the unique
effectsof eachestablishmentareexcluded.A log
likelihood ratio test shows that the variables
reportedin Table 2 significantly improve the
model fit (chi(28) = 405.66; p < .001), as compared with the baseline models that have no
variablesrepresentingdiversityprograms(available on request).
ORGANIZATIONALRESPONSIBILITY.Coefficients for the diversityprogramsrepresentthe
change in the log odds that managersare from
a certaingroup that is attributableto the presence of a practice,averagedacross all years of
the program'sexistence.Afteremployersset up
affirmativeactionplans,the odds for whitemen
in managementdecline by 8 percent;the odds
for whitewomenrise by 9 percent;andthe odds
for blackmen rise by 4 percent.These numbers
represent the estimated average difference
CORPORATE
AFFIRMATIVE
ACTIONANDDIVERSITY
POLICIES 603
Table2. FixedEffectsEstimatesof the Log Oddsof WhiteMen andWomenandBlackWomenandMen in
Management,1971-2002
Organizational
Responsibility
Affirmativeactionplan
Diversitycommittee
Diversitystaff
ManagerialBias
Diversitytraining
Diversityevaluations
SocialIsolation
Networkingprograms
Mentoringprograms
LegalEnvironment
Governmentcontract
Compliancereview
TitleVII lawsuit
EEOCcharge
Structures
Organizational
Proportionmanagersin establishment
size (log)
Establishment
Unionagreement
Formalpersonnelpolicies
In-houseattorney
policy
Targetedrecruitment
Work-familyaccommodations
TopManagementComposition
Proportionminoritiesin top management
Proportionwomenin top management
WhiteMen
WhiteWomen
BlackWomen
BlackMen
-.078**
(.017)
-.081**
(.028)
-.055
(.033)
.086**
(.017)
.175**
(.029)
.104**
(.034)
.005
(.014)
.242**
(.024)
.123**
(.028)
.039*
(.015)
.114**
(.026)
.128**
(.030)
-.038
(.021)
.028
(.027)
-.001
(.022)
.061*
(.028)
-.066**
(.018)
-.027
(.023)
.031
(.019)
-.081**
(.025)
-.083**
(.027)
-.011
(.033)
.080**
(.028)
-.004
(.035)
.012
(.023)
.213**
(.029)
-.096**
(.024)
.037
(.031)
.032
(.019)
-.083**
(.020)
-.107**
(.015)
-.007
(.016)
.006
(.019)
.077**
(.020)
.141**
(.016)
.014
(.017)
-.039*
(.016)
.020
(.017)
.044**
(.013)
.019
(.014)
-.027
(.017)
.081**
(.018)
.029*
(.014)
.034*
(.015)
-.896**
(.108)
-.021
(.012)
-.053
(.033)
-.002
(.004)
-.100**
(.023)
-.071**
(.021)
-.078**
(.008)
.309**
(.112)
-.023*
(.012)
-.068*
(.034)
-.003
(.004)
.126**
(.024)
.108**
(.021)
.065**
(.009)
-4.499**
(.092)
-.661**
(.010)
-.007
(.028)
-.016**
(.003)
-.040*
(.020)
.131**
(.018)
.026**
(.007)
-3.989**
(.099)
-.515**
(.011)
-.029
(.030)
-.015**
(.003)
.021
(.021)
.099**
(.019)
.004
(.008)
-.002
(.001)
-.002**
(.001)
-.002
(.001)
.004**
(.001)
.007**
(.001)
.002**
(.001)
.012**
(.001)
-.002*
(.001)
.2799
.3636
.3335
.3146
R2(64 parameters)
=
<
unrelated
.001.
Data
shown
are
coefficients
from
Note: Log likelihoodratiotest;X2(28) 405.66;p
seemingly
regressionwith standarderrorsin parentheses.Variablesincludedin the analysesbutnot shownhereare8 vari4 binaryvariablesforproportionof eachgroupin non-managerial
jobs andin corejob in eachestablishment;
ablesfor no workersfroma groupin management;8 variablesforproportionof eachgroupin stateandindustry
rate(full
laborforces;proportionof contractorfirmsin industry;industryemployment;andstateunemployment
resultson OnlineSupplement,ASRWebsite:http://www2.asanet.org/journals/asr/2006/toc052.html).
Analyses
also includeestablishmentandyearfixed effects.All independentvariablesarelaggedby 1 year,excluding
= 16,265;N (organizations)
= 708. EEOC= Equal
proportionof managerialjobs. N (organization-year)
Employment Opportunity Commission. * p < .05; ** p < .01 (two tailed test).
604
AMERICANSOCIOLOGICALREVIEW
between having a plan and the counterfactual
condition of not having a plan for the entire
periodof the plan'sexistence.These resultsare
consistent with Leonard's(1990) finding that
affirmativeactionplangoals areeffective.Note
thatthe coefficient for black women is not significant here. When we introduced industry
interactions,we discoveredthatin manufacturing (computers, electronics, transportation),
affirmative action plans had negative effects
on black women, whereas in service (retail,
insurance,businessservices),affirmativeaction
planshadpositiveeffects (resultsavailableupon
request).Creatinga diversitycommitteeincreases the odds for white women, acrossthe period
of the committee's existence, by 19 percent.
The odds for black women rise 27 percent,and
the odds for black men rise 12 percent.
Employerswho appointfull-timediversitystaff
also see significant increases in the odds for
white women (11 percent), black women (13
percent), and black men (14 percent) in management.
As noted,the coefficientsin Table2 represent
the averagechanges in log odds thatmanagers
are from a certain group. The effect of each
programon the percentof women and minorities in management will vary depending on
where organizationsbegin (Fox 1997:78). For
example, an 8 percent decrease in the odds of
managersbeing whitemen resultingfromadoption of affirmativeaction plan would translate
to a decline of 2.6 percent in the percent of
whitemen in managementif they constituted70
percent before adoption, but it would mean a
larger decline of 4.3 percent if they made up
only 50 percent at the baseline (Petersen
1985:311).
PROGRAMSFORREDUCINGMANAGERIAL
BIAS.
Programsdesigned to reduce managerialbias
througheducation(diversitytraining)andfeedback (diversity evaluations)show one modest
positive effect and two negative effects across
the threedisadvantagedgroups.Diversitytraining is followedby a 7 percentdeclinein the odds
for blackwomen. Diversityevaluationsarefollowed by a 6 percentrise in the odds for white
women, but an 8 percentdecline in the odds for
black men. These mixed effects are anticipated
in the literature.As noted,laboratorystudiesand
surveys often show adversereactionsto training (Bendick et al. 1998; Nelson et al. 1996).
Moreover, critics argue that trainers define
diversitybroadlyto includegroupsnot covered
by federal civil rights law (parents,smokers),
and therebydrawattentionaway from protected groups (Edelman, Fuller, and Mara-Drita
2001; Kochanet al. 2003; KonradandLinnehan
1995).
PROGRAMSFOR REDUCINGSOCIALISOLATION.
Networkingandmentoringprograms,designed
to countersocial isolation,show modest effects
on managerialdiversity.Networkingis followed
by a rise in the odds for white women and a
decline in the odds for white men and black
men. The negativecoefficient for black men is
anticipatedby qualitativeresearch(Carter2003;
Friedmanand Craig2004) showingthatwhites
can develop negativeattitudestowardAfricanAmerican organizing. In contrast, mentoring
programsshow a strongpositive effect on the
odds for black women. These findings suggest
that having personal guidance and supportat
workcan facilitatecareerdevelopment(Castilla
2005) for blackwomen, whereasnetworkingis
more effective for white women.
GENDER AND RACIAL PATTERNS.Overall, it
appears that diversity programs do most for
white women and more for black women than
for black men. Black men gain significantly
less from affirmative action than do white
women (chi-sq(1) = 4.15, p < .05), and significantly less from diversitycommitteesthan do
blackwomen(chi-sq(l) = 22.47,p.< .01). Three
programs show negative effects on African
Americans,whereasno programshows a negative effect on white women. We hesitate to
overinterpretthis pattern,but note thatthere is
somethingof a trade-offamong groups.
Table3 evaluatesthe magnitudeof the effects
of programson the proportionof each groupin
managementbased on the coefficients in Table
2. "Proportionin year of adoption"is the mean
proportion of each group in management,
amongadopters,in theiractualyearsof program
adoption(i.e.,just beforetreatment)."Estimated
proportionwith practice"shows the predicted
mean proportionafter the practice is in place.
Thus, for example, the proportion of white
women among managersin the averageestablishment adopting an affirmative action program was 0.132, and the net effect of the
CORPORATE
AFFIRMATIVE
ACTION
ANDDIVERSITY
POLICIES 605
Table3. EstimatedAverageDifferencesin ManagerialCompositionDue to Adoptionof AffirmativeActionand
DiversityPractices
WhiteMen
AffirmativeActionPlan
.783
Proportionin yearof adoption
Estimatedproportionwith practice
.769
Percentdifferencedue to adoption
-1.8%**
DiversityCommittee
.630
Proportionin yearof adoption
Estimatedproportionwith practice
.611
Percentdifferencedueto adoption
-3.0%**
DiversityStaff
.724
Proportionin yearof adoption
Estimatedproportionwith practice
.713
Percentdifferencedueto adoption
-1.5%
DiversityTraining
.687
Proportionin yearof adoption
Estimatedproportionwith practice
.679
Percentdifferencedueto adoption
-1.2%
DiversityEvaluations
.720
Proportionin yearof adoption
Estimatedproportionwith practice
.726
Percentdifferencedueto adoption
.8%
NetworkingPrograms
.702
Proportionin yearof adoption
Estimatedproportionwithpractice
.684
Percentdifferencedueto adoption
-2.6%**
MentoringPrograms
.690
Proportionin yearof adoption
Estimatedproportionwith practice
.688
Percentdifferencedueto adoption
-.3%
Note:Estimatesbasedon coefficientspresentedin Table2.
* p < .05; ** p < .01 (twotailedtest).
program,with control for other factors, is to
raise white women proportion to 0.142.
Similarly,theproportionof blackwomenamong
managerswas 0.014 in the averagefirm adopting a diversitycommittee,and adoptionbrings
black women to 0.018, an increase of almost
30%.The thirdrow,basedon the firsttwo rows,
reportsthe percentagechangeoverthe baseline
resultingfrom programadoption.
Tables 2 and 3 supportour contention that
programsestablishingorganizationalresponsibility aremorebroadlyeffective thanthose that
address managerial bias or social isolation
among women and African Americans.
Organizationsthat structureresponsibilitysee
consistent positive effects for white women,
black women, and black men.
Coefficients for control variables are consistent with expectations, with one possible
exception. The negative effect of formal per-
WhiteWomen
BlackWomen
BlackMen
.132
.142
7.6%**
.017
.017
.0%
.024
.025
4.2%**
.230
.262
13.9%**
.014
.018
29.8%**
.020
.022
10.0%**
.157
.171
8.9%**
.014
.016
14.3%**
.021
.024
14.3%**
.194
.194
.0%
.017
.016
-5.9%**
.022
.023
4.5%
.160
.168
5.0%
.017
.017
.0%
.024
.022
-8.3%**
.193
.206
6.7%**
.014
.014
.0%
.020
.018
-10.0%**
.017
.021
23.5%**
.021
.022
4.8%
.216
.215
-.5%
sonnel policies is not consistentwith the idea
that bureaucracyimpedes cronyism or bias in
promotion decisions (Reskin and McBrier
2000), but is consistentwith the argumentthat
formalizationleads to the needless inflationof
educationalprerequisites(Collins 1979), and
with findings that the determinantsof promotion differsystematicallyfor whites andblacks
even when formal personnel systems exist
(BaldiandMcBrier1997). Othercoefficientsof
control variables show that although growth
and unionizationhave not improveddiversity,
andalthoughlegal staffhadonly limitedeffects,
targeted recruitment programs, work/family
accommodations,and top managementteam
diversity show positive effects on managerial
diversity.Coefficients for the labormarketand
economic environmentmeasures, not shown
here, are in the expected directionas well (see
Online Supplement,ASRWeb site).
606
AMERICAN
SOCIOLOGICAL
REVIEW
DOEs ORGANIZATIONAL
RESPONSIBILITY
IMPROVEPROGRAMEFFECTIVENESS?
It is possible that some programswork best in
combination with others (MacDuffie 1995;
Perry-Smithand Blum 2000). Ourfinding that
organizational responsibility structureshave
broadereffects than other programssuggests
that perhaps training, evaluation, mentoring,
and networkingwould be more successful in
combinationwith responsibilitystructures.We
undertakeseveral analyses of programcombinations.
First,we explorethe possibility thatthe simple numberof programsmatters.Perhapsour
measurescapturenot the effects of discreteprogramsso much as an orientationtowardchanging workplacedemography.We introducethree
thepresenceof any
binaryvariablesrepresenting
and
three
or
more
one, two,
programs.Across
the 16,265 organization-yearspells of data,49
percent had no programs,34 percent had one
program,10 percenthad two programs,and 7
percenthad threeor moreprograms.In the top
panel of Table 4, we reportthe effects of the
Table4. Fixed-EffectsEstimatesof the Log Oddsof WhiteMen andWomenandBlackWomenandMenin
Managementwith Bundlesof Programs,1971-2002
Adoptionof One or MoreAA Plans& DiversityPrograms
Onlyone program
Twoprograms
Threeor moreprograms
R2(60 parameters)
Interactionwith ResponsibilityStructures
Responsibilitystructures
Diversitytraining
x Responsibilitystructure
Diversityevaluations
x Responsibilitystructure
Networkingprograms
x Responsibilitystructure
Mentoringprograms
x Responsibilitystructure
White
Men
White
Women
Black
Women
Black
Men
-.043**
(.016)
-.091**
(.023)
-.158**
(.029)
.056**
(.016)
.121**
(.023)
.232**
(.030)
-.009
(.013)
.020
(.019)
.127**
(.025)
.026
(.014)
.024
(.021)
.046
(.027)
.3323
.3124
.3569
.2767
-.063**
(.017)
-.026
(.036)
-.026
(.042)
.294**
(.057)
-.326**
(.061)
-.090
(.050)
-.003
.081**
(.017)
-.064
(.038)
.132**
(.043)
-.042
(.059)
.136*
(.063)
.163**
(.052)
-.088
.007
(.014)
-.046
(.031)
.044
(.036)
-.065
(.049)
.057
(.053)
-.026
(.043)
.073
.042**
(.015)
.026
(.033)
.040
(.038)
-.077
(.052)
.009
(.057)
-.172*
(.046)
.118*
(.056)
(.058)
(.048)
(.051)
.140**
(.066)
-.183*
(.074)
-.101
(.068)
.133
(.076)
-.042
(.057)
.344**
(.063)
.127*
(.061)
-.108
(.068)
R2(66 parameters)
.3347
.3136
.3602
.2785
Data
shown
are
coefficients
from
2
unrelated
with
standard
in
errors
seemingly
regressionanalyses
parenNote.:
theses.ResponsibilityStructuresincludeaffirmativeactionplans,diversitycommitteesanddiversitystaff.The
analysesincludeestablishmentandyearfixed effectsandall the controlvariablesincludedin the modelspresented in Table2 (forcoefficientsof controlvariables,see OnlineSupplement,
ASRWebsite:http://www2.
N (organization-year)
= 16,265;N (organizations)=708.
asanet.org/journals/asr/2006/toc052.html).
* p < .05; ** p < .01
(two tailed test).
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
numberof programsin models parallelto those
presentedin Table2 (resultsfor the controlvariables are availableon the Online Supplement,
ASRWebsite).Wecomparedcoefficientsforthe
binary count variablesusing t tests. For white
women,the sheernumberof programsmatters;
one is betterthanzero, two betterthanone, and
three or more are better than two. For white
men, we find the opposite pattern,suggesting
that each additionalprogramreduces the odds
for white men. Forblackwomen, havingone or
two programsis not significantlydifferentfrom
having none. Havingthree is significantly different. For black men, none of the count variablesshowan effect significantlydifferentfrom
havingno programs.Hence, for white women,
the more programsthe better. For blacks, the
numberof programsmattersless thanthe contentof theprograms.This is not surprisinggiven
that some practicesin Table2 show no effects,
or even negative effects, on blacks.
Althougheachadditionalprogram,regardless
of content,does not alwaystranslateintogreater
diversity,particularbundlesof programsmight
operatewell together.To test this idea, we ran
(in models otherwiseidenticalto those in Table
2) all two-way interactionsbetween affirmative action plan, diversitycommittee,diversity
staff,training,evaluation,networking,andmentoring.(The bivariatecorrelationsandjoint frequenciesof the sevenprogramsarepresentedon
the Online Supplement, ASR Web site.) The
two-way interactionsamong training, evaluation,networking,andmentoringdidnot indicate
that any pairs operatedbetter than individual
programs. But two-way interactions with
responsibility structuresdid render training,
evaluation, networking, and mentoring more
effective. Forease of presentation,we collapse
the three responsibilitystructuresinto a single
variable,interactingit with the four otherprogram variables. The second panel in Table 4
includesestimatesfrommodelswiththese interactions(resultsfor the controlvariablesarepresented on the Online Supplement,ASR Web
site).
Diversity training, evaluation, networking,
and mentoringprogramsare more effective in
firms with responsibilitystructures.Withdiversity trainingand evaluations,the responsibility
structure interaction positively affects white
women. With networking, the responsibility
structure interaction positively affects black
607
men, and with mentoring,it positively affects
blackwomen.Note thatthe noninteractedvariable,responsibilitystructure,continuesto show
the expected effects for white men, white
women, and black men. The overallpatternis
strikingand suggeststhatthese authoritystructuresrenderthe otherprogramsmore effective.
Yeteven with responsibilitystructuresin place,
none of these programsshow the sort of consistent pattern across outcomes that we find
for, say, diversitycommittee.
Do AFFIRMATIVE
ACTIONORDERS
MEDIATE
PROGRAM
EFFICACY?
In Table2, we also examine whetheraffirmative action enforcement shows direct effects.
Employers who sign a government contract,
andtherebybecomesubjectto affirmativeaction
regulation,do not see increases in managerial
diversityas a directresult.Whenwe interacted
contractorstatuswith theperiod1971-1980, the
results did not supportearly researchers'findings thatcontractorsexperiencedfastergrowth
in black employmentin the 1970s. Of course,
effects foundin earlierstudieswere quitesmall,
and it may be that they were concentratedin
industrieswe do not sample.Forthe entireperiod, we find a decline in the odds for black
women afterthe approvalof a governmentcontract.This maybe becauseemployerswho strive
to improvetheir numbersbefore seeking government work, improve more slowly after
receiving contracts (Baron et al. 1991:1389;
Leonard1990:65). Governmentcontractorstatus does not showpositiveeffects even whenwe
exclude programsthat may be associatedwith
contractorstatus:the seven diversitymeasures,
formalHR policies, work-family policies, and
compliance reviews (results available on
request).
Unlike contractorstatus, antidiscrimination
enforcementshows effects. Federalcompliance
reviews, which 32 percentof the contractorsin
ourdatafaced,increasedrepresentation
of white
women and black men. Leonard(1985b) also
foundeffectsof compliancereviewsin his study
of the 1970s. When we interactedcompliance
review with the period 1971-1980, our results
(availableupon request)replicatedhis finding
from the 1970s as well (see also Kalev and
Dobbin forthcoming).Discriminationlawsuits
increase the odds for all three groups in man-
608
AMERICAN
SOCIOLOGICAL
REVIEW
agement (Skaggs 2001), and EEOC charges
increasethe odds for black men.
The naturalfollow-up question is whether
affirmativeaction oversightmediatesthe efficacy of the seven affirmativeaction and diversity measures. Theory suggests that program
implementationmaybe takenmoreseriouslyin
firms subjectto regulatoryscrutiny.Thosefirms
typicallyassignresponsibilityfor complianceto
an office or person. In Table5, we add interaction terms between programs and contractor
status to the model presented in Table 2.
Coefficients for controlvariablesare available
on the Online Supplement,ASR Web site. A
Table 5.
log-likelihoodtest showsa significantimprovement in fit over that of the model presentedin
Table 2. The interaction coefficients show
whethereffectsaresignificantlydifferentamong
contractorsand noncontractors.We also examine the linear combination of the interaction
components (using Lincom in Stata)to assess
whether programs have significant effects
among contractors.
Diversity trainingshows the greatestdifference in effects on all four groups. Whereas
among noncontractorstraining decreases the
representationof white and black women in
management,among contractorsit is followed
Fixed-Effects Estimates of the Log Odds of White Men and Women and Black Women and Men in
Management with Government Contractor Interactions, 1971-2002
Affirmative Action Plan
X Government contract
Diversity Committee
X Government contract
Diversity Staff
X Government contract
Diversity Training
X Government contract
Diversity Evaluations
X Government contract
Networking Programs
X Government contract
Mentoring Programs
X Government contract
R2 (71 parameters)
White Men
White Women
Black Women
-.050*
(.023)
-.050
(.028)
-.096*
(.038)
.029
(.053)
-.076
(.058)
.024
(.066)
.005
(.027)
-.092*
(.038)
.049
(.039)
-.041
(.050)
-.133**
(.038)
.086**
(.023)
.003
(.029)
.173**
(.040)
-.006
(.055)
.018
(.060)
.120
(.068)
-.094**
(.028)
.197**
(.040)
.090*
(.041)
-.035
(.051)
.171**
(.039)
-. 195**
(.052)
-.053
(.047)
.086
(.065)
.000
(.019)
.000
(.024)
.270**
(.033)
-.050
(.046)
.205**
(.050)
-.127*
(.056)
-. 116**
(.023)
.107**
(.033)
-.097**
(.034)
.118**
(.042)
-.034
(.033)
.069
(.043)
.179**
(.039)
.057
(.054)
(.053)
-.145*
(.060)
-.016
(.025)
.100**
(.035)
-.063
(.036)
-.027
(.045)
-.035
(.035)
-.113*
(.046)
.070
(.042)
-.056
(.058)
.3165
.3650
.2811
.111*
(.051)
.028
(.046)
-.081
(.063)
.3341
Black Men
.007
(.021)
.053*
(.026)
.076*
(.035)
.074
(.049)
.240**
Note. Log likelihood ratio test; X2(28) = 135.86; p < .001; Data shown are coefficients from seemingly unrelated
regression with standarderrors in parentheses. The analyses include establishment and year fixed effects and all
the control variables included in the models presented in Table 2 (for coefficients of control variables, see Online
Supplement, ASR Web site: http://www2.asanet.org/journals/asr/2006/toc052.html). N (organization-year)=
16,265; N (organizations)= 708.
* p < .05; ** < .01
p
(two tailed test).
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
by a significant decline in the odds for white
men (3 = .086; SE = .004) and significant
increasesamongwhite women (3 =. 103; SE =
.030) and black men (3 = .083; SE = .027).
Diversityevaluationsalso areless likelyto backfire among contractors, where the effect on
black women is now zero.
Affirmativeaction plans show significantly
largereffects for blackmen amongcontractors,
furthersupportingLeonard's(1990) findings.
The coefficients for diversitystaff in the models for black women and men, althoughsignificantly smaller among contractors, are still
positiveandsignificant(B = .078; SE = .032 and
B = .095; SE = .034, respectively).Networking
programshelp white women in noncontractor
establishments,at the expenseof whitemen,but
this effect disappearsamong contractors,and
black men see negativeeffects for reasonsthat
are not clear.
FURTHERANALYSES
A key challenge in analysis of nonexperimental data is to account for heterogeneity that
stemsfromnonrandomselectionintothe "treatment" (in our case, adopting a program).
Heterogeneitymay bias casual inference. Our
model specification,with fixed effects for each
year and each establishmentand with control
variablesmeasuringorganizationalstructures,
laborpool composition,andeconomicand legal
environment,is designedto minimize this possibility.
We conducted three additional robustness
tests (results available on request). First, we
addedbinaryvariablesas proxies for unspecified, unobserved events (impending lawsuit,
local news coverage) that may have caused
employersboth to implementnew antidiscriminationprogramsand to hire more women and
AfricanAmericans.We createdproxiesfor each
of the seven programs.We re-ranthe analysis
14 times, with proxies measured2 and 3 years
before programadoptionin models parallelto
thosepresentedin Table2. Theseproxyvariables
did not substantiallyalter the coefficients or
standarderrorsfor affirmativeactionanddiversity programs,and most did not show significanteffects.This addsto ourconfidencethatthe
observed relationshipsbetween diversity programsandmanagerialdiversityarenot spurious
609
(Rossi, Lipsey, and Freeman 2004; Snyder
2003).
Second, programadoptersmay be different
fromnonadoptersin ways thatarenot absorbed
by the establishment fixed effects. Perhaps
adopters change faster than nonadopters in
terms of managementfads and demographics.
We therefore re-ran the analyses in Table 2
seventimes, eachtime only with establishments
thateveradopteda particularprogram(once for
affirmativeactionplan adopters,then for diversity committee,etc.). If the effects in Table2 are
attributable
to differencesbetweenadoptersand
nonadopters,then programeffects should disappear when we exclude nonadopters. The
resultsof our"adoptersonly"analysesare substantivelysimilarto those in Table2.
Third,we were concernedthat because the
datasetis not rectangular(some establishments
enter the data after 1971), unobservedheterogeneity might distort the results if establishments are missing in early years for reasons
(e.g. organizationalsize or age) associatedwith
the outcome variables.We thus replicatedthe
analysisusing a rectangularsubsampleof establishments.The resultswere substantiallysimilar to those reportedin this discussion.
To examine the robustnessof the results to
within-unitserial correlation,we correctedfor
thepossibilitythateacherroris partiallydependent on the errorof the previous year (AR[1])
with the Cochrane-Orcuttmethod(availablein
State using xtregar,not the seemingly unrelated regression).This transformsthe databy subtractingfromthe equationfortime t the equation
for time t-1 multiplied by the autocorrelation
coefficient. The AR(1) results are substantially similarto those reportedin Table2 (available
on the Online Supplement,ASRWebsite). The
one exception is that affirmativeaction plan is
significant for whites only at thep < 0.1 level.
Wereportseeminglyunrelatedregressionmodels in Table2 because they accountfor relatedness of outcome variables and are thus more
efficient, andbecausethey allow us to compare
coefficients for differentgroups.
Because our analyses cover more thanthree
decades, we also exploredtwo theories of timing and programefficacy (results availableon
request)to ruleoutthe possibilitythatsome programsshowingno effects in the aggregateactually were effective at certain points in time.
One theoryis thatemployerpracticesaremore
6io
AMERICAN
SOCIOLOGICAL
REVIEW
effective under active regulatoryregimes. We
thus added to the model reported in Table 2
interactiontermsbetweeneach of the practices
andthe Reaganand first Bush era(1981-1992)
as well as the Bill Clintonand GeorgeW.Bush
era (1993-2002). The comparisonperiod,1971
to 1980,encompassedthe activistNixon administration,the brief Fordadministration,and the
activistCarteradministration(Skrentny1996).
A finding that programswere more effective
during the 1970s might help to explain why
research on the period (e.g., Leonard 1990)
found the greatest increases in black employment among contractors.We find no evidence
thatprogramsoperateddifferentlyacross periods.
The second timing argument is that early
programadoptersare those most committedto
change (Tolbertand Zucker 1983). We looked
at whether the effects of each practice were
strongeramong the first 15, 25, and40 percent
of eventualadopters.Ouranalysesshowedthat
practices are no more effective among early
adopters.
We also explored whether some programs
showedweak effects in the modelsbecausethey
had differential effects by establishmentsize
or industry.With regard to size interactions,
some negative programeffects were neutralized in very large establishments,but the programsthatprovedineffectivein generalwerenot
effectiveamonglargeor smallorganizations.In
industryinteractions,mostprogrameffectswere
stable in direction if not in magnitudeacross
industries. One notable pattern was that the
effect of affirmative action plans on black
womenwas negativein manufacturingandpositive in service, as discussed earlier.
Finally, we were concerned that survey
respondentreportsof earlyprogramdatesmight
be inaccurate,which could cause us to underestimate program effects by including posttreatment values (i.e., that reflect changes
attributableto a program)as pretreatmentdata.
We were particularlyconcerned about results
showing weak effects for training,evaluations,
networking, and mentoring. Correlations
between respondenttenureand adoptionyears
were small and not significant, the one exception being for networking(correlationof-0.20;
p < 0.05). To evaluatethe effects of measurement error,we re-ranTable 2 models, eliminating establishment-yearspells before 1990,
thus excluding fromthe analysispossibly erroneous informationon early years of adoption.
Using fixed-effectsmodelsto analyzeonly data
for 1990-2002 would preventus from evaluating the effects of programsadopted any time
before 1990, so we firstreplicatedthe full analysis (for the entireperiod) without fixed establishmenteffects,replacingdifferencedvariables
with undifferencedvariables.The results were
similarto thosepresentedin Table2. Thenusing
the undifferencedvariables,we re-ranthe models eliminating all establishment-yearspells
before 1990. We lost many spells, but the substantiveresultsheld up (for results, see Online
Supplementon ASR Web site). This increases
our confidence in the models, and particularly
in the weak effects of training,evaluations,networking,and mentoring.
CONCLUSION
The antidiscrimination
measureswe studyhave
become popular among employers, HR managers,lawyers,andadvocacygroups,despitethe
absenceof hardevidencethattheywork(BisomRapp1999;Krawiec2003). Employersuse these
practices to defend themselves in court, and
the courts,in many cases, acceptthem as good
faith efforts to stamp out discrimination
(Edelman et al. 2005). There are reasons to
believe that employers adopt antidiscrimination measuresas window dressing,to inoculate
themselves against liability, or to improve
moraleratherthanto increasemanagerialdiversity. In the final analysis,however,the measure
of these programs-for scholars,practitioners,
andthe courts-should be whetherthey do anythingto increasediversity.Using EEO-1reports,
we cannot examine whether these programs
help womenandAfricanAmericansto move up
fromthe bottomrungsof management.But we
can show thatsome populardiversityprograms
at least help women andAfricanAmericansto
climb intothe ranksof management.Otherpopularprogramsdo not do even that.
Thereis a richtraditionof theoryandresearch
on the causes of workplaceinequality.We contend that this work may not always hold clear
implicationsfor remedies.The questionof how
to reduceinequalityis just as deservingof attention. Ourconceptualizationof differenttypes of
diversity programsand our analyses of their
effects lay the groundworkfor researchandthe-
CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES
ory on the remediationof inequalityin workplaces.
Broadly speaking,our findings suggest that
althoughinequalityin attainmentat work may
be rootedin managerialbias andthe social isolation of women and minorities,the best hope
for remedyingit may lie in practicesthatassign
organizationalresponsibility for change. Our
own theory of the remediation of inequality
builds on classical organizational sociology
ratherthanon theoriesof cognitivebias or social
networks(see also Blum, Fields, andGoodman
1994).
Structuresthatembedaccountability,authority, and expertise (affirmative action plans,
diversitycommittees and taskforces,diversity
managersanddepartments)arethe most effective means of increasing the proportions of
white women, black women, and black men in
private sector management. Moreover, they
show effectseven in the presenceof controlsfor
the specific initiatives that specialists often
implement,from formalhiring and promotion
rules to work-familyprograms.Responsibility
structuresalso catalyzethe otherdiversityprograms, renderingeach a bit more effective for
one group. Some programs also prove more
effective among federal contractors, likely
because legal requirementsencourageemployers to assign responsibilityfor compliance.
Practicesthattargetmanagerialbias through
feedback(diversityevaluations)and education
(diversitytraining)show virtuallyno effect in
the aggregate. They show modest positive
effects when responsibilitystructuresare also
in place and among federal contractors.But
they sometimes show negative effects otherwise. Researchto datefromHR expertsandpsychologists suggests that interactive training
workshops,of the kind we examine, often generate backlash. Finally,programsdesigned to
counter the social isolation of women and
minorities throughmentoringand networking
are disappointing, although mentoring does
appearto help black women.
The poor performance of practices that
address social-psychological and social-relational sourcesof inequalityshouldnot be taken
as evidence that these forces do not produce
social inequality.A preponderanceof empirical
researchshows thatbias andpoornetworkconnections contribute to inequality. Further
611
researchis needed to determinewhy these programs do not live up to theirpromise.
Much managementtheorizingfrom law and
economics scholars (Becker 1968; Gray and
Shadbegian 2005; Posner 1992; see also
Simpson2002) andpsychologists (e.g. Tetlock
1985) suggests that corporatebehavioris best
controlledby doling out incentives to individual managersand shapingtheir attitudes.This
approachis rooted in a sort of methodological
individualismthatis prominentin management
researchandpractice.However,when it comes
to addressingcorporateinequalitywe find that
the strategies designed to change individuals
are less effective than the conventionalmanagementsolutionof settinggoals andassigning
responsibilityfor moving towardthese goals.
Thatsaid,the threeprogramswe foundto be
most effective likely operatein somewhatdifferentways. Whereasaffirmativeaction plans
anddiversitystaffbothcentralizeauthorityover
and accountabilityfor workforcecomposition,
diversity committees locate authority and
accountabilityin an interdepartmental
taskforce
andmay workby causingpeople fromdifferent
partsof the organizationto take responsibility
for pursuingthe goal of integration.
In this study,we examinemanagersalone. It
is important for both theory and practice to
extend this research to other occupational
groups.Yet for employersseeking solutions to
the problem of gender and racial segregation,
our analyses offer hope. Most employers do
something to promote diversity-76 percent
had adopted one of these seven programsby
2002-but do they do what is most effective?
Diversitycommitteeshavebeen quiteeffective,
requiringneitheradditionalstaffnor expensive
consultants.Less than 20 percentof the establishments we studied had them by 2002.
Diversitystaff are also quite effective, but only
11 percentof establishmentshad them. On the
otherhand,diversitytraining,which 39 percent
of establishmentshad adopted,and which can
be quite costly, was not very effective and
showedadverseeffects amongnoncontractors.
Even the programsthatworkbest havemodest effects, particularlyfor AfricanAmericans,
who are poorly represented to begin with.
Diversity committees raise the proportionof
black women in managementby a remarkable
30 percent on average,but from a baseline of
only 1.4 percent.Appointingfull-time diversi-
612
AMERICANSOCIOLOGICALREVIEW
ty staffer raises the proportion of black men by
a healthy 14 percent, but from a baseline of
only 2.1 percent. These programs alone will
not soon change the look of management. Note,
however, that our sample of large, private firms
has changed less quickly than the economy as
a whole. In young start-up firms and in the public sector, these practices may be even more
effective than they are in our sample.
The effects of these programs should not be
conflated with the effects of antidiscrimination
legislation. First, as we demonstrate, federal
affirmative action regulations clearly mediate
the efficacy of diversity evaluations and training. Our findings thus go against the popular
claim that antidiscrimination regulation is no
longer needed because diversity programs have
gained a life of their own (Fisher 1985;
Liberman2003). Moreover,it was federalregulations that led employers to first establish
affirmative action plans, the most common
interventionand one of the most effective.
Second, enforcement has been effective
regardless of corporate policies. As research
has shown,andas ourfindingssupport,TitleVII
lawsuits and affirmative action compliance
reviewsled to increasesin women'sandminorities' share of managementjobs, especially in
periodsandjudicialcircuitswhereincivil rights
enforcement was strong (Kalev and Dobbin
forthcoming;
Leonard 1989; 1990; Skaggs
2001).
Finally, to assess the impact of antidiscrimination legislation on employment inequality,
one needs to consider broader political, social,
and cultural changes associated with the Civil
Rights Act, affirmative action, and related laws
(Burstein 2000). Yet if the effects of government
antidiscrimination measures have slowed, as
some observers suggest, then we should waste
no time sorting out which corporate programs
are effective.
Alexandra Kalev received her Ph.D. from Princeton
in 2005. Her dissertation examines how workplace
restructuring ("high performance" systems and
downsizing) affects the careers of women and minorities. Kalev is a postdoctoral fellow in the Robert
Wood Johnson Scholars in Health Policy Research
Program at UC Berkeley studying gender and racial
disparities in work related injuries and illnesses.
Kalev has published with Frank Dobbin on civil
rights law enforcement in the face of deregulation
(Law and Social Inquiry), and with Erin Kelly on how
companies manage flexible
Economic Review).
schedules
(Socio-
Frank Dobbin is Professor of Sociology at Harvard.
He edited The New Economic Sociology: A Reader
(Princeton University Press) and The Sociology of
the Economy (Russell Sage Foundation), both published in 2004. He is continuing work with Kalev and
Kelly on the effects of employer policies on workforce
diversity, and is spending the 2006-2007 academic
year at the Radcliffe InstituteforAdvanced Study, with
fellowships from Radcliffe and from the John Simon
Guggenheim Foundation.
Erin L. Kelly is Assistant Professor of Sociology at
the University of Minnesota. Her research on the
development, diffusion, and implementation of family-supportive policies has appeared in the American
Journal of Sociology and the SocioEconomic Review.
She and Phyllis Moen are conducting a multimethod
study of whether and how flexible work initiatives
affect organizational cultures, the experiences of
workers on the job, and the health and well-being of
workers and their families. Thatproject is part of the
National Institutes of Health s research network on
work, family, health, and well-being.
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