Experimental Analysis of Gender Bias in Hiring within STEM Fields

This study investigates the presence of gender bias in students' hiring evaluations within STEM fields using a survey-based experimental design with systematically varied resumes. Students were randomly assigned to evaluate one of four fictional CVs, differing by candidate gender and qualification strength. Participants rated the applicants on competence, hireability, salary recommendation, and willingness to offer professional support. The results reveal no consistent bias in favor of male candidates; however, strong male applicants received higher salary suggestions, while female candidates were more likely to be offered professional support. These patterns are primarily driven by interactions between candidate gender and resume strength. The effects are most pronounced among participants from Eastern Europe and older participants, suggesting a role of social background in shaping perceptions. The findings highlight how implicit biases may form prior to labor market entry and underscore the need for early educational interventions to promote equitable hiring perceptions in STEM.

Authors

Institutions

Publication Details

Journal
Universitätsbibliothek der LMU
Published
2026-09-15
DOI
https://doi.org/10.5282/jums/v11i3pp598-610
Primary Topic
Names, Identity, and Discrimination Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Experimental Analysis of Gender Bias in Hiring within STEM Fields

Roya Kazimova
Universitätsbibliothek der LMU
Names, Identity, and Discrimination Research
article

Experimental Analysis of Gender Bias in Hiring within STEM Fields

Roya Kazimova
article en

Abstract

This study investigates the presence of gender bias in students' hiring evaluations within STEM fields using a survey-based experimental design with systematically varied resumes. Students were randomly assigned to evaluate one of four fictional CVs, differing by candidate gender and qualification strength. Participants rated the applicants on competence, hireability, salary recommendation, and willingness to offer professional support. The results reveal no consistent bias in favor of male candidates; however, strong male applicants received higher salary suggestions, while female candidates were more likely to be offered professional support. These patterns are primarily driven by interactions between candidate gender and resume strength. The effects are most pronounced among participants from Eastern Europe and older participants, suggesting a role of social background in shaping perceptions. The findings highlight how implicit biases may form prior to labor market entry and underscore the need for early educational interventions to promote equitable hiring perceptions in STEM.

Universitätsbibliothek der LMU
Technical University of Munich (DE)
Gender equality
Openalex Percentile: Top 4%
Names, Identity, and Discrimination Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.