Author(s): Alexander Ugarov
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The paper describes a potential platform to facilitate academic peer review with emphasis on early-stage research. This platform aims to make peer review more accurate and timely by rewarding reviewers on the basis of peer prediction algorithms. The algorithm uses a variation of Peer Truth Serum for Crowdsourcing Radanovic et al. (2016) with human raters competing against a machine learning benchmark. We explain how our approach addresses two large productive inefficiencies in science: mismatch between research questions and teams and redundancy of research projects. Better peer-review for early research creates additional incentives for sharing it, which simplifies matching ideas to teams and reduces redundancy.
Published: 2022-11-17 19:43:29 PT
Stage: Work-in-progress
Fields: Digital Economics
Research Group(s): Playground
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