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Cross-replication Reliability -- An Empirical Approach to Interpreting Inter-rater Reliability

Published 11 Jun 2021 in stat.AP, cs.AI, and cs.SI | (2106.07393v1)

Abstract: We present a new approach to interpreting IRR that is empirical and contextualized. It is based upon benchmarking IRR against baseline measures in a replication, one of which is a novel cross-replication reliability (xRR) measure based on Cohen's kappa. We call this approach the xRR framework. We opensource a replication dataset of 4 million human judgements of facial expressions and analyze it with the proposed framework. We argue this framework can be used to measure the quality of crowdsourced datasets.

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