arXiv cs.CY· Uttamasha Anjally Oyshi, Gibson Nkhata, Susan Gauch·· 11 小时前AI 评分20
arXiv 撤稿论文：学术同行评审中作者人口特征的因果分析
Causal Analysis of Author Demographics in Academic Peer Review
AI 导读
一篇基于 530 篇论文的因果推断研究发现，少数族裔作者在评审排名中平均承受 -0.42 分的因果劣势，女性作者为 -0.25 分，全球南方机构作者为 -0.57 分。该研究以发表场所声望作为评审排名的替代指标，指出传统与 AI 评审流程均需公平性干预。该投稿已被 arXiv Admin 以不符合研究内容质量标准为由撤稿。
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Abstract:Academic meritocracy is jeopardized by systematic imbalances; for example, whereas Black and Hispanic individuals constitute over 30% of the U.S. population, they represent fewer than 10% of tenured academics in science and engineering. Peer review serves as a crucial gatekeeper in this process, however it encounters ongoing issues over biases that may hinder scientific advancement. The issue is now exacerbated by the growing influence of artificial intelligence (AI) in academic assessment. This paper transcends correlation to quantitatively assess the independent impacts of author demographics, including race, gender, and country of affiliation, on paper acceptance rankings. We utilize a causal inference methodology on a dataset of 530 papers, simulating the academic selection process by employing the prestige of the publication venue as a surrogate for review rank. Our research indicates statistically substantial causal disadvantages for authors from minority racial groups (average treatment effects [ATE]: -0.42 points in ranking), female authors (ATE: -0.25), and those associated with institutions in the Global South (ATE: -0.57). The exhibited biases emphasize the pressing necessity for fairness interventions in both conventional and AI-based review processes, indicating that such measures are essential for establishing a more equitable and credible scientific environment.
| Comments: | arXiv admin note: This submission has been withdrawn because it does not meet arXiv's research content quality standards |
| Subjects: | Computers and Society (cs.CY) |
| Cite as: | arXiv:2603.06641 [cs.CY] |
| (or arXiv:2603.06641v2 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2603.06641 arXiv-issued DOI via DataCite |
Submission history
From: arXiv Admin [view email]
[v1]
Wed, 25 Feb 2026 21:43:13 UTC (468 KB)
[v2]
Thu, 29 Oct 2026 20:01:41 UTC (1 KB) (withdrawn)
来源：arXiv cs.CY · arxiv.org