Disparities in Peer Review Tone and the Role of Reviewer Anonymity
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866912492834258944 |
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| author | Sahakyan, Maria AlShebli, Bedoor |
| author_facet | Sahakyan, Maria AlShebli, Bedoor |
| contents | The peer review process is often regarded as the gatekeeper of scientific integrity, yet increasing evidence suggests that it is not immune to bias. Although structural inequities in peer review have been widely debated, much less attention has been paid to the subtle ways in which language itself may reinforce disparities. This study undertakes one of the most comprehensive linguistic analyses of peer review to date, examining more than 80,000 reviews in two major journals. Using natural language processing and large-scale statistical modeling, it uncovers how review tone, sentiment, and supportive language vary across author demographics, including gender, race, and institutional affiliation. Using a data set that includes both anonymous and signed reviews, this research also reveals how the disclosure of reviewer identity shapes the language of evaluation. The findings not only expose hidden biases in peer feedback, but also challenge conventional assumptions about anonymity's role in fairness. As academic publishing grapples with reform, these insights raise critical questions about how review policies shape career trajectories and scientific progress. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_14741 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Disparities in Peer Review Tone and the Role of Reviewer Anonymity Sahakyan, Maria AlShebli, Bedoor Computation and Language The peer review process is often regarded as the gatekeeper of scientific integrity, yet increasing evidence suggests that it is not immune to bias. Although structural inequities in peer review have been widely debated, much less attention has been paid to the subtle ways in which language itself may reinforce disparities. This study undertakes one of the most comprehensive linguistic analyses of peer review to date, examining more than 80,000 reviews in two major journals. Using natural language processing and large-scale statistical modeling, it uncovers how review tone, sentiment, and supportive language vary across author demographics, including gender, race, and institutional affiliation. Using a data set that includes both anonymous and signed reviews, this research also reveals how the disclosure of reviewer identity shapes the language of evaluation. The findings not only expose hidden biases in peer feedback, but also challenge conventional assumptions about anonymity's role in fairness. As academic publishing grapples with reform, these insights raise critical questions about how review policies shape career trajectories and scientific progress. |
| title | Disparities in Peer Review Tone and the Role of Reviewer Anonymity |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2507.14741 |