  Many recent studies have probed status bias in the peer-review process of
academic journals and conferences. In this article, we investigated the
association between author metadata and area chairs' final decisions
(Accept/Reject) using our compiled database of 5,313 borderline submissions to
the International Conference on Learning Representations (ICLR) from 2017 to
2022. We carefully defined elements in a cause-and-effect analysis, including
the treatment and its timing, pre-treatment variables, potential outcomes and
causal null hypothesis of interest, all in the context of study units being
textual data and under Neyman and Rubin's potential outcomes (PO) framework. We
found 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%) were
less favored by area chairs compared to their matched counterparts. The results
were 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 a
strengthened design). We discussed how to interpret these results in the
context of multiple interactions between a study unit and different agents
(reviewers and area chairs) in the peer-review system.
