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Implicit biases and gender gaps in the assessment of job candidates
Last registered on February 22, 2021


Trial Information
General Information
Implicit biases and gender gaps in the assessment of job candidates
Initial registration date
February 20, 2021
Last updated
February 22, 2021 12:04 PM EST

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Primary Investigator
Other Primary Investigator(s)
PI Affiliation
University of Bonn
Additional Trial Information
On going
Start date
End date
Secondary IDs
Researchers have documented gender gaps in many labor market outcomes, such as hiring and admission decisions or the evaluation of performance. This study aims at understanding the role of gender biases among interviewers as potential drivers of gender gaps in hiring outcomes. Moreover, we plan to analyze the impact of a ‘bias awareness’ intervention that aims at reducing the gender gap in the assessment of candidates applying to a large company.
External Link(s)
Registration Citation
Radbruch, Jonas and Amelie Schiprowski. 2021. "Implicit biases and gender gaps in the assessment of job candidates." AEA RCT Registry. February 22. https://doi.org/10.1257/rct.7072-1.0.
Experimental Details
The intervention is a workshop module conducted with interviewers in the treatment group. The module targets gender biases regarding the cognitive and math abilities of female candidates. As part of the module, interviewers participate in a Gender-Science Implicit Association Test (Greenwald et al., 2009) and get direct feedback on their score. Moreover, interviewers in the treatment group receive short re-freshers before each interview phase. Due to the pandemic, the entire intervention takes place online.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Assessment of candidate’s cognitive abilities (average cognitive score)
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Assessment of candidate’s non-cognitive skills (average non-cognitive score)
Recommendation to hire candidate (0/1)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The study has two goals: (1) estimate the relationship between an interviewer’s implicit gender attitudes and her assessment behavior; (2) evaluate the effect of an intervention targeting gender biases. The intervention includes a workshop module and regular refreshers (as described above). We will evaluate the effect of being assigned to an interviewer in the treatment group (interacted with candidate gender) on the assessment. We plan to evaluate the effect both through simple post-intervention differences and a diff-in-diff framework analyzing within-interviewer (team) variation over time.
Experimental Design Details
Not available
Randomization Method
We randomize at the interviewer team level. To balance interviewer team characteristics, we first build pairs of interviewer teams and then randomly assign one team per pair to treatment and the other to the control group, using the ‘nbpMatching’ R package.
Randomization Unit
Interviewer Team
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
1000-1500 interviews for the intervention period, depending on the number of applicants and conducted interviews (outside researchers’ control). About 7,000 interviews for the pre-intervention period.
Sample size (or number of clusters) by treatment arms
The treatment group consists of 6 clusters, the control group of 5 clusters.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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