Abstract
Black and Hispanic faculty – underrepresented minorities (URMs) within academia – face career barriers that come to a crux in promotion and tenure decisions. Leveraging a natural experiment in choice architecture within a dataset of 1804 promotion and tenure decisions across six universities, we find that joint (906 faculty) vs. separate (898 faculty) evaluation reduces racial disparities in faculty outcomes. Specifically, in joint evaluation, an analysis of the simple slopes finds that Black and Hispanic faculty receive, on average, 9% fewer negative votes at the department level than in separate evaluations when controlling for research productivity, school, gender, rank, discipline, department size, and grant acquisition. Using moderated mediation analyses, we calculate that this translates into a 16.2% increase in the likelihood of a Black/Hispanic faculty member receiving a promotion. In a survey of 289 professors who have served on promotion and tenure committees (i.e., the key P&T decision-makers), we find that only 17% of faculty expect joint evaluation to improve underrepresented minority faculty outcomes and, conversely, 43% expect separate evaluation to improve underrepresented minority faculty outcomes. This natural experiment suggests that altering evaluation mode or simulating joint evaluation mode could help address academia’s underrepresentation problem, but not in the way decision-makers expect.
Data availability
The forecasting survey and natural experiment data generated in this study have been deposited in the Open Science Framework (OSF) database accessible at: https://doi.org/10.17605/OSF.IO/JUX2C. The natural experiment uses the Center for Excellence in Faculty Advancement (CEFA) dataset66, used previously by Masters-Waage et al.2. Due to the high sensitivity of this data, the raw natural experiment is not available to protect the privacy of the promotion candidates in the dataset. However, a modified version of the dataset is available, omitting the US news ranking variable, as this would allow readers to identify each institution, and standardizing variables such as h-index to protect the privacy of the P&T candidates. This partial subset of the data is available at the OSF page.
Code availability
The forecasting survey and natural experiment analysis code has been deposited in the Open Science Framework (OSF) database accessible at: https://doi.org/10.17605/OSF.IO/JUX2C.
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Acknowledgements
We gratefully acknowledge our grantors, including The Alfred P. Sloan Foundation and The National Science Foundation (NSF #1409928 (C.S.), NSF #2100034 (J.M.), and NSF #2411941 (C.S.)). Note that funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We would also like to thank our entire team within the promotion and tenure collaborative research consortium and our External Advisory Board members, who support the consortium.
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T.M.W., J.M.M, and C.S. are jointly responsible for the conceptualization of this study and funding acquisition. T.M.W. wrote the original draft, and T.M.W., J.M.M, M.G., A.G., E.E, H. Y., and C.S. jointly contributed to reviewing and editing the draft. T.M.W., E.E., P.L., and H. Y. are responsible for methodology, analyses, and data visualization. J.M.M. and C.S. supervised the project.
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Masters-Waage, T.C., Madera, J.M., Edema-Sillo, E. et al. Evaluating multiple candidates simultaneously reduces racial disparities in promotion and tenure. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69937-5
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DOI: https://doi.org/10.1038/s41467-026-69937-5
