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; Michael Schaerer; Christilene Du Plessis; My Hoang Bao Nguyen; Robbie C.M.Van Aert; Leo Tiokhin; Daniel Lakens; Elena Giulia Clemente; Thomas Pfeiffer; Anna Dreber; Magnus Johannesson; Cory J. Clark; Birte Siem

doi:10.1016/j.obhdp.2023.104280

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

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

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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; Schaerer, Michael; Plessis, Christilene Du et al.
in: Organizational Behavior and Human Decision Processes, Jahrgang 179, 104280, 01.11.2023.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Bibtex

@article{896b8e43b5714c12b5e06bc0ee98b787,

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

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.",

keywords = "Discrimination, Field experiments, Forecasting, Gender, Meta-analysis, Open science",

author = "{Gender Audits Forecasting Collaboration} and Michael Schaerer and Plessis, {Christilene Du} and Nguyen, {My Hoang Bao} and Aert, {Robbie C.M.Van} and Leo Tiokhin and Daniel Lakens and Clemente, {Elena Giulia} and Thomas Pfeiffer and Anna Dreber and Magnus Johannesson and Clark, {Cory J.} and Uhlmann, {Eric Luis} and Abraham, {Ajay T.} and Magdalena Adamus and Cinla Akinci and Federica Alberti and Alsharawy, {Abdelaziz M.} and Shilaan Alzahawi and Frederik Anseel and Felix Arndt and Binnur Balkan and Ernest Baskin and Bearden, {Carrie E.} and Benotsch, {Eric G.} and Stefan Bernritter and Black, {Sheila R.} and Wiebke Bleidorn and Boysen, {Andrew P.} and Brienza, {Justin P.} and Mitch Brown and Brown, {Stephanie E.V.} and Brown, {Joshua W.} and Jeffrey Buckley and Brett Buttliere and Nick Byrd and Hynek C{\'i}gler and Taba{\'r}e Capitan and Paolo Cherubini and Chong, {Shao Yuan} and Ciftci, {Esma Esen} and Conrad, {Cheryl D.} and Paul Conway and Elaine Costa and Cox, {Jolene A.} and Cox, {Daniel J.} and Francisco Cruz and Dawson, {Ian G.J.} and Demiral, {Elif E.} and Derrick, {Jaye L.} and Birte Siem",

note = "Publisher Copyright: {\textcopyright} 2023 The Authors",

year = "2023",

month = nov,

day = "1",

doi = "10.1016/j.obhdp.2023.104280",

language = "English",

volume = "179",

journal = "Organizational Behavior and Human Decision Processes",

issn = "0749-5978",

publisher = "Academic Press Inc.",

}

RIS

TY - JOUR

T1 - On the trajectory of discrimination

T2 - A meta-analysis and forecasting survey capturing 44 years of field experiments on gender and hiring decisions

AU - Gender Audits Forecasting Collaboration

AU - Schaerer, Michael

AU - Plessis, Christilene Du

AU - Nguyen, My Hoang Bao

AU - Aert, Robbie C.M.Van

AU - Tiokhin, Leo

AU - Lakens, Daniel

AU - Clemente, Elena Giulia

AU - Pfeiffer, Thomas

AU - Dreber, Anna

AU - Johannesson, Magnus

AU - Clark, Cory J.

AU - Uhlmann, Eric Luis

AU - Abraham, Ajay T.

AU - Adamus, Magdalena

AU - Akinci, Cinla

AU - Alberti, Federica

AU - Alsharawy, Abdelaziz M.

AU - Alzahawi, Shilaan

AU - Anseel, Frederik

AU - Arndt, Felix

AU - Balkan, Binnur

AU - Baskin, Ernest

AU - Bearden, Carrie E.

AU - Benotsch, Eric G.

AU - Bernritter, Stefan

AU - Black, Sheila R.

AU - Bleidorn, Wiebke

AU - Boysen, Andrew P.

AU - Brienza, Justin P.

AU - Brown, Mitch

AU - Brown, Stephanie E.V.

AU - Brown, Joshua W.

AU - Buckley, Jeffrey

AU - Buttliere, Brett

AU - Byrd, Nick

AU - Cígler, Hynek

AU - Capitan, Tabaŕe

AU - Cherubini, Paolo

AU - Chong, Shao Yuan

AU - Ciftci, Esma Esen

AU - Conrad, Cheryl D.

AU - Conway, Paul

AU - Costa, Elaine

AU - Cox, Jolene A.

AU - Cox, Daniel J.

AU - Cruz, Francisco

AU - Dawson, Ian G.J.

AU - Demiral, Elif E.

AU - Derrick, Jaye L.

AU - Siem, Birte

PY - 2023/11/1

Y1 - 2023/11/1

N2 - 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.

AB - 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.

KW - Discrimination

KW - Field experiments

KW - Forecasting

KW - Gender

KW - Meta-analysis

KW - Open science

UR - http://www.scopus.com/inward/record.url?scp=85176269117&partnerID=8YFLogxK

U2 - 10.1016/j.obhdp.2023.104280

DO - 10.1016/j.obhdp.2023.104280

M3 - Journal articles

AN - SCOPUS:85176269117

VL - 179

JO - Organizational Behavior and Human Decision Processes

JF - Organizational Behavior and Human Decision Processes

SN - 0749-5978

M1 - 104280

ER -

DOI

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

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