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The stigma of affirmative action: : A stereotyping- based theory and meta-analytic test of the consequences for performance.
Abstract
Affirmative action plans (AAPs) are designed to facilitate workplace success for members of the groups they target (e.g., women, ethnic minorities), yet may have the ironic effect of stigmatizing AAP targets and, in turn, decreasing their performance outcomes. Prior work has focused on the stigma of incompetence as the primary mechanism that links AAPs to performance; however, the broader social psychological literature suggests that additional mechanisms may also play a role. We use stereotyping theories to develop a more comprehensive model of the pathways through which AAPs limit targets' performance outcomes. Drawing from the stereotype content model, we propose that the negative effect of AAPs on others' evaluations of targets' performance is driven by perceptions of incompetence and low warmth. Drawing from stereotype threat theory, we propose that the negative effect of AAPs on targets' self-evaluated and objective performance is driven by perceptions of low self-competence, negative state affect, and perceived stereotyping by others. Meta-analytic path analyses support our hypotheses. Our theory and findings demonstrate that multiple mechanisms explain the negative consequences of AAPs for targets' performance outcomes, highlight differences in reactions to AAP targets by others versus the self, and provide insight into preventing the unintended negative effects of AAPs.
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“This is in support of prior research which has found that, despite the best intentions of organizational leaders, many diversity efforts fail to benefit underrepresented groups and can instead harm the intended beneficiaries or lead to other unintended consequences (Kalev et al. 2006, Plaut et al. 2011, Leslie et al. 2014, Dobbin and Kalev 2016, Cardador 2017, Leslie 2019).”
From Included but undermined: How representation goals backfire (2025) · cites this paper as Leslie et al. 2014
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Reactions to Employment Equity Programs and Situational Interviews: A Laboratory Study
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Affirmative Action: How Can We Be So Lost When We Don't Even Know Where We Are Going?
Kovach, K. A., Kravitz, D. A., & Hughes, A. A. (2004) · Labor law journal · Cited by 13
Self-citationThe Role of Self‐Perceptions in Reactions to Preferential and Merit‐Based Hiring1
Hattrup, K. (1998) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.1998.tb01703.x · Cited by 7
Ironic Effects of Flexible Work Practices on Parents' Career Success
Leslie, L. M., Manchester, C. F., & Dahm, P. C. (2013) · Academy of Management Proceedings · doi:10.5465/ambpp.2013.66 · Cited by 2
Self-citation
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Cited by
A Multi-Level Process Model for Understanding Diversity Practice Effectiveness
Nishii, L. H., Khattab, J., Shemla, M., & Paluch, R. M. (2018) · Academy of Management Annals · doi:10.5465/annals.2016.0044 · Cited by 233
Tackling Educational Inequalities with Social Psychology: Identities, Contexts, and Interventions
Easterbrook, M. J., & Hadden, I. R. (2021) · Social Issues and Policy Review · doi:10.1111/sipr.12070 · Cited by 110
Included but undermined: How representation goals backfire
Osborne, M. R., Roberson, J. W., & Tost, L. (2025) · doi:10.31234/osf.io/cse5r_v2
Metadata
- Authors
- Leslie, L. M., Mayer, D. M., & Kravitz, D. A.
- Affiliations
- New York University
- University of Michigan
- George Mason University
- Venue
- Academy of Management Journal
- Publisher
- Academy of Management
- Published
- 2014-08
- Volume
- 57
- Issue
- 4
- Pages
- 964-989
- ISSN
- 0001-4273
- 1948-0989
- Cited by
- 183
- References
- 130
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.