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On the trajectory of discrimination: A meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions

  • Gender Audits Forecasting Collaboration
  • Singapore Management University
  • Tilburg University
  • Eindhoven University of Technology
  • Stockholm School of Economics
  • University of Innsbruck
  • INSEAD
  • IG&H
  • Seattle University
  • Masaryk University
  • University of St Andrews
  • University of Portsmouth
  • Princeton University
  • Stanford University
  • University of New South Wales
  • University of Guelph
  • Stockholm University
  • Saint Josephs University
  • University of California at Los Angeles
  • Virginia Commonwealth University
  • King's College London
  • University of Alabama
  • University of Zurich
  • University of North Carolina at Chapel Hill
  • University of Queensland
  • University of Arkansas
  • ICF International
  • Indiana University Bloomington
  • Technological University of the Shannon: Midland Midwest
  • University of Warsaw
  • Stevens Institute of Technology
  • Swedish University of Agricultural Sciences
  • University of Milan - Bicocca
  • Anadolu University
  • Tunku Abdul Rahman University College
  • Arizona State University
  • University of Southampton
  • University of Utah
  • University of the Sunshine Coast
  • University of Manchester
  • University of Lisbon
  • Austin Peay State University
  • University of Houston

Research output: Contribution to journalArticlepeer-review

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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 male-stereotypical 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.

Original languageEnglish
Article number104280
JournalOrganizational Behavior and Human Decision Processes
Volume179
Early online date10 Nov 2023
DOIs
Publication statusPublished - Nov 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 5 - Gender Equality
    SDG 5 Gender Equality

ASJC Scopus subject areas

  • Applied Psychology
  • Organizational Behavior and Human Resource Management

Keywords

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

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