Short abstract

Using machine learning to analyze 39,458 peer review reports submitted to the national Swiss funder, we examined how gender and discipline relate to grant peer review content. We found substantive differences between female and male reviewers and across research fields.

Long abstract

Peer review by experts in the field is the cornerstone of the scientific review process. This study examined how gender and disciplinary norms shape the content and tone of grant peer review. We analyzed 39,458 review reports submitted to the Swiss National Science Foundation between 2016 and 2023, covering 11,409 applications for project funding across 21 disciplines from the Social Sciences and Humanities (SSH), Life Sciences (LS), and Mathematics, Informatics, Natural Sciences, and Technology (MINT). Using supervised machine learning, we classified over 1.3 million sentences by evaluation criteria and sentiment. Reviews in SSH were significantly longer and more critical, while those in MINT were more concise and positive. Female reviewers write longer and more structured reviews and are slightly more positive than their male counterparts. There were substantial differences across fields and disciplines, suggesting that disciplinary conventions strongly influence review practices. Our findings have implications for fairness, transparency, and consistency in research evaluation systems.