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Peer Prediction for Peer Review: Designing a Marketplace for Ideas

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  • Alexander Ugarov

Abstract

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 publication bias. Better peer review for early research creates additional incentives for sharing it, which simplifies matching ideas to teams and makes negative results and p-hacking more visible.

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  • Alexander Ugarov, 2023. "Peer Prediction for Peer Review: Designing a Marketplace for Ideas," Papers 2303.16855, arXiv.org.
    • Handle: RePEc:arx:papers:2303.16855
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    References listed on IDEAS

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