Litcius/Paper detail

Gender bias in funding evaluation: A randomized experiment

Laura Cruz Castro, Luís Sanz Menéndez

2023Quantitative Science Studies13 citationsDOIOpen Access PDF

Abstract

Abstract Gender differences in research funding exist, but bias evidence is elusive and findings are contradictory. Bias has multiple dimensions, but in evaluation processes, bias would be the outcome of the reviewers’ assessment. Evidence in observational approaches is often based either on outcome distributions or on modeling bias as the residual. Causal claims are usually mixed with simple statistical associations. In this paper we use an experimental design to measure the effects of a cause: the effect of the gender of the principal investigator (PI) on the score of a research funding application (treatment). We embedded a hypothetical research application description in a field experiment. The subjects were the reviewers selected by a funding agency, and the experiment was implemented simultaneously with the funding call’s peer review assessment. We manipulated the application item that described the gender of the PI, with two designations: female PI and male PI. Treatment was randomly allocated with block assignment, and the response rate was 100% of the population, avoiding problems of biased estimates in pooled data. Contrary to some research, we find no evidence that male or female PIs received significantly different scores, nor any evidence of same-gender preferences of reviewers regarding the applicants’ gender.

Topics & Concepts

Observational studyRandomized experimentGender biasAgency (philosophy)PsychologySelection biasPopulationOutcome (game theory)Publication biasInformation biasMeta-analysisResearch designReporting biasSocial desirability biasActuarial scienceEconometricsSocial psychologyDemographyStatisticsMedicineMEDLINEPolitical scienceEconomicsMathematicsSocial desirabilitySociologySocial scienceInternal medicineLawMathematical economicsAdvanced Causal Inference Techniquesscientometrics and bibliometrics researchMeta-analysis and systematic reviews