Abstract

A preregistered meta-analysis, including 244 effect sizes from 85 field audits and 361,645 individual job applications, tested for gender bias in hiring practices in female-stereotypical and gender-balanced as well as malestereotypical jobs from 1976 to 2020. A “red team” of independent experts was recruited to increase the rigor and robustness of our meta-analytic approach. A forecasting survey further examined whether laypeople (n = 499 nationally representative adults) and scientists (n = 312) could predict the results. Forecasters correctly anticipated reductions in discrimination against female candidates over time. However, both scientists and laypeople overestimated the continuation of bias against female candidates. Instead, selection bias in favor of male over female candidates was eliminated and, if anything, slightly reversed in sign starting in 2009 for mixed-gender and male-stereotypical jobs in our sample. Forecasters further failed to anticipate that discrimination against male candidates for stereotypically female jobs would remain stable across the decades.

Keywords

Gender; Discrimination; Field experiments; Meta-analysis; Open science; Forecasting

Published in

Organizational Behavior and Human Decision Processes
2023, Volume: 179, article number: 104280

SLU Authors

• Capitán Jimenéz, Tabaré

  • Department of Economics, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Gender Studies


Publication identifier

DOI: https://doi.org/10.1016/j.obhdp.2023.104280

Permanent link to this page (URI)

https://res.slu.se/id/publ/127105