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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

On the trajectory of discrimination: a meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions
On the trajectory of discrimination: a meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions
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.
Field experiments, Gender, discrimination, forecasting, meta-analysis, open science, Discrimination, Open science, Forecasting, Meta-analysis
0749-5978
Schaerer, Michael
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du Plessis, Christilene
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Nguyen, My Hoang Bao
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van Aert, Robbie C.M.
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Tiokhin, Leo
bccebfb4-072c-4ce1-888e-db91a1343b4e
Lakens, Daniël
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Clemente, Elena Giulia
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Pfeiffer, Thomas
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Dreber, Anna
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Johannesson, Magnus
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Clark, Cory J.
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Uhlmann, Eric Luis
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Dawson, Ian G.J.
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Conway, Paul
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Gender Audits Forecasting Collaboration
Schaerer, Michael
58228b50-93ae-49b1-be04-52628ee71c55
du Plessis, Christilene
da8de395-e014-4566-9505-14c9b5df92cf
Nguyen, My Hoang Bao
f3e0dff2-f744-409d-9185-61d7b2cecb74
van Aert, Robbie C.M.
16a62e9b-553d-428c-ae08-11934335723d
Tiokhin, Leo
bccebfb4-072c-4ce1-888e-db91a1343b4e
Lakens, Daniël
404eed8d-d0ee-4cca-b2c3-f89b5f92a3ee
Clemente, Elena Giulia
f8adeff4-f452-48b1-aeaf-d18f5f2bc206
Pfeiffer, Thomas
1c70e479-9a56-46ea-8863-a8d28adbd07a
Dreber, Anna
8026beca-9fa1-42af-8fc5-bf08b10cd14d
Johannesson, Magnus
d12ffaac-27f2-4e3c-8899-56388b62bcc3
Clark, Cory J.
f175df35-b95d-4f45-bea1-121fbe2dd527
Uhlmann, Eric Luis
cc58096d-e069-4e2f-be6d-303b2d5b671e
Dawson, Ian G.J.
dff1b440-6c83-4354-92b6-04809460b01a
Conway, Paul
765aaaf9-173f-44cf-be9a-c8ffbb51e286

Schaerer, Michael, du Plessis, Christilene, Nguyen, My Hoang Bao, van Aert, Robbie C.M., Tiokhin, Leo, Lakens, Daniël, Clemente, Elena Giulia, Pfeiffer, Thomas, Dreber, Anna, Johannesson, Magnus, Clark, Cory J. and Uhlmann, Eric Luis , Gender Audits Forecasting Collaboration (2023) On the trajectory of discrimination: a meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions. Organizational Behavior and Human Decision Processes, 179, [104280]. (doi:10.1016/j.obhdp.2023.104280).

Record type: Article

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.

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The Trajectory of Discrimination - OBHDP - Nov 2023 - Version of Record
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Accepted/In Press date: 4 September 2023
e-pub ahead of print date: 10 November 2023
Published date: 10 November 2023
Additional Information: Publisher Copyright: © 2023 The Authors
Keywords: Field experiments, Gender, discrimination, forecasting, meta-analysis, open science, Discrimination, Open science, Forecasting, Meta-analysis

Identifiers

Local EPrints ID: 484323
URI: http://eprints.soton.ac.uk/id/eprint/484323
ISSN: 0749-5978
PURE UUID: 492e348a-33fc-47c0-8af1-8951cc91497b
ORCID for Ian G.J. Dawson: ORCID iD orcid.org/0000-0003-0555-9682
ORCID for Paul Conway: ORCID iD orcid.org/0000-0003-4649-6008

Catalogue record

Date deposited: 15 Nov 2023 18:09
Last modified: 18 Mar 2024 04:09

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Contributors

Author: Michael Schaerer
Author: Christilene du Plessis
Author: My Hoang Bao Nguyen
Author: Robbie C.M. van Aert
Author: Leo Tiokhin
Author: Daniël Lakens
Author: Elena Giulia Clemente
Author: Thomas Pfeiffer
Author: Anna Dreber
Author: Magnus Johannesson
Author: Cory J. Clark
Author: Eric Luis Uhlmann
Author: Ian G.J. Dawson ORCID iD
Author: Paul Conway ORCID iD
Corporate Author: Gender Audits Forecasting Collaboration

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