The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
The mixed effects of online diversity training
Open accessAbstract
Significance: Although diversity training is commonplace in organizations, the relative scarcity of field experiments testing its effectiveness leaves ambiguity about whether diversity training improves attitudes and behaviors toward women and racial minorities. We present the results of a large field experiment with an international organization testing whether a short online diversity training can affect attitudes and workplace behaviors. Although we find evidence of attitude change and some limited behavior change as a result of our training, our results suggest that the one-off diversity trainings that are commonplace in organizations are not panaceas for remedying bias in the workplace.
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The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Measuring individual differences in implicit cognition: the implicit association test
Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.74.6.1464 · Cited by 9,210
Understanding and using the Implicit Association Test: III. Meta-analysis of predictive validity.
Greenwald, A. G., Poehlman, T. A., Uhlmann, E. L., & Banaji, M. R. (2009) · Journal of Personality and Social Psychology · doi:10.1037/a0015575 · Cited by 3,257
Kalev, A., Dobbin, F., & Kelly, E. (2006) · American Sociological Review · doi:10.1177/000312240607100404 · Cited by 2,052
A Brief Social-Belonging Intervention Improves Academic and Health Outcomes of Minority Students
Walton, G. M., & Cohen, G. L. (2011) · Science · doi:10.1126/science.1198364 · Cited by 1,992 · cited 1×
“These strategies include targeting the specific underlying psychological process believed to produce undesirable outcomes (13), offering personalized feedback about individuals’ own biases to motivate change (14), destigmatizing attempts to improve on undesirable behaviors (15, 16), and offering actionable strategies…”
BackgroundIntention-to-treat concept: A review
Gupta, S. (2011) · Perspectives in Clinical Research · doi:10.4103/2229-3485.83221 · Cited by 1,921
Sexism and racism: Old-fashioned and modern prejudices
Swim, J. K., Aikin, K. J., Hall, W. S., & Hunter, B. A. (1995) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.68.2.199 · Cited by 1,486
Prejudice Reduction: What Works? A Review and Assessment of Research and Practice
Paluck, E. L., & Green, D. P. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.60.110707.163607 · Cited by 1,376
The bias blind spot: perceptions of bias in self versus others
Pronin, E., Lin, D. Y., & Ross, L. (2002) · Personality and Social Psychology Bulletin · doi:10.1177/0146167202286008 · Cited by 1,289
Long-term reduction in implicit race bias: A prejudice habit-breaking intervention
Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. T. L. (2012) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2012.06.003 · Cited by 1,259
Cited by
Prejudice Reduction: Progress and Challenges
Paluck, E. L., Porat, R., Clark, C. S., & Green, D. P. (2021) · Annual Review of Psychology · doi:10.1146/annurev-psych-071620-030619 · Cited by 686
Gender bias in academia: A lifetime problem that needs solutions
Llorens, A., Tzovara, A., Bellier, L., Bhaya-Grossman, I., Bidet-Caulet, A., Chang, W. K., Cross, Z. R., Dominguez-Faus, R., Flinker, A., Fonken, Y., et al. (2021) · Neuron · doi:10.1016/j.neuron.2021.06.002 · Cited by 361
Using large language models in psychology
Demszky, D., Yang, D., Yeager, D. S., Bryan, C. J., Clapper, M., Chandhok, S., Eichstaedt, J. C., Hecht, C., Jamieson, J., Johnson, M., et al. (2023) · Nature Reviews Psychology · doi:10.1038/s44159-023-00241-5 · Cited by 369
Men, women and STEM: Why the differences and what should be done?
Stewart-Williams, S., & Halsey, L. G. (2021) · European Journal of Personality · doi:10.1177/0890207020962326 · Cited by 117
Faculty Perspectives on UDL: Exploring Bridges and Barriers for Broader Adoption in Higher Education
Hills, M., Overend, A., & Hildebrandt, S. (2022) · The Canadian Journal for the Scholarship of Teaching and Learning · doi:10.5206/cjsotlrcacea.2022.1.13588 · Cited by 55
Metadata
- Authors
- Chang, E. H., Milkman, K. L., Gromet, D. M., Rebele, R. W., Massey, C., Duckworth, A. L., & Grant, A. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2019-04
- Volume
- 116
- Issue
- 16
- Pages
- 7778-7783
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2928191607
- Cited by
- 304
- References
- 32
- FWCI
- 67.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Chang, E. H., Milkman, K. L., Gromet, D. M., Rebele, R. W., Massey, C., Duckworth, A. L., & Grant, A. M. (2019). The mixed effects of online diversity training. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1816076116
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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