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Gendered Language in Job Advertisements Relates to Gender Sorting in Public Labor Markets: A Multi-Source Analysis

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  • Sievert, Martin

    (Leiden University)

  • Vogel, Dominik

    (Harz University of Applied Sciences)

  • Döring, Matthias

Abstract

While increasing gender diversity is a desirable goal, contemporary research often overlooks gender sorting in the public labor market. Such structural self-selection among job seekers may considerably weaken efforts to increase diversity. We investigate how job advertisements contribute to gender sorting by examining gendered language and the gender of the contact person. We theorize two mechanisms and test them using a unique multi-source dataset consisting of real job advertisements, a survey among recruiters issuing these job advertisements, and organization-level data (n = 1,859). Results from hierarchical linear models indicate that more feminine wording relates to a higher number and share of applications by women. Our research contributes to public administration research, theorizing why, structurally, women may apply less for some public sector jobs. We derive implications for research and policymakers and emphasize the relevance of gender sorting mechanisms in public sector recruiting.

Suggested Citation

  • Sievert, Martin & Vogel, Dominik & Döring, Matthias, 2024. "Gendered Language in Job Advertisements Relates to Gender Sorting in Public Labor Markets: A Multi-Source Analysis," SocArXiv u6z5e_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:u6z5e_v1
    DOI: 10.31219/osf.io/u6z5e_v1
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    References listed on IDEAS

    as
    1. Michael A. Stoll & Steven Raphael & Harry J. Holzer, 2004. "Black Job Applicants and the Hiring Officer's Race," ILR Review, Cornell University, ILR School, vol. 57(2), pages 267-287, January.
    2. Peter Kuhn & Kailing Shen, 2023. "What Happens When Employers Can No Longer Discriminate in Job Ads?," American Economic Review, American Economic Association, vol. 113(4), pages 1013-1048, April.
    3. Sievert, Martin, 2023. "Sievert (2023): The Limited Impact of Reference Groups’ Symbolic Gender Representation on Willingness to Coproduce," OSF Preprints r2s95, Center for Open Science.
    4. Dominik Vogel & Matthias Döring & Martin Sievert, 2024. "Motivational signals in public sector job advertisements and how they relate to attracting and hiring candidates," Public Management Review, Taylor & Francis Journals, vol. 26(10), pages 2868-2900, October.
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