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Many recent studies have probed status bias in the peer-review process ofacademic journals and conferences. In this article, we investigated theassociation between author metadata and area chairs' final decisions(Accept/Reject) using our compiled database of 5,313 borderline submissions tothe International Conference on Learning Representations (ICLR) from 2017 to2022. We carefully defined elements in a cause-and-effect analysis, includingthe treatment and its timing, pre-treatment variables, potential outcomes andcausal null hypothesis of interest, all in the context of study units beingtextual data and under Neyman and Rubin's potential outcomes (PO) framework. Wefound some weak evidence that author metadata was associated with articles'final decisions. We also found that, under an additional stability assumption,borderline articles from high-ranking institutions (top-30% or top-20%) wereless favored by area chairs compared to their matched counterparts. The resultswere consistent in two different matched designs (odds ratio = 0.82 [95% CI:0.67 to 1.00] in a first design and 0.83 [95% CI: 0.64 to 1.07] in astrengthened design). We discussed how to interpret these results in thecontext of multiple interactions between a study unit and different agents(reviewers and area chairs) in the peer-review system.

Association between author metadata and acceptance: A feature-rich, matched observational study of a corpus of ICLR submissions between 2017-2022