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Auctions and Prediction Markets for Scientific Peer Review
arXiv - CS - Computer Science and Game Theory Pub Date : 2021-08-27 , DOI: arxiv-2109.00923
Siddarth Srinivasan, Jamie Morgenstern

Peer reviewed publications are considered the gold standard in certifying and disseminating ideas that a research community considers valuable. However, we identify two major drawbacks of the current system: (1) the overwhelming demand for reviewers due to a large volume of submissions, and (2) the lack of incentives for reviewers to participate and expend the necessary effort to provide high-quality reviews. In this work, we adopt a mechanism-design approach to propose improvements to the peer review process. We present a two-stage mechanism which ties together the paper submission and review process, simultaneously incentivizing high-quality reviews and high-quality submissions. In the first stage, authors participate in a VCG auction for review slots by submitting their papers along with a bid that represents their expected value for having their paper reviewed. For the second stage, we propose a novel prediction market-style mechanism (H-DIPP) building on recent work in the information elicitation literature, which incentivizes participating reviewers to provide honest and effortful reviews. The revenue raised by the Stage I auction is used in Stage II to pay reviewers based on the quality of their reviews.

中文翻译:

科学同行评审的拍卖和预测市场

同行评审的出版物被认为是证明和传播研究界认为有价值的想法的黄金标准。然而,我们发现当前系统的两个主要缺点:(1)由于提交量大,对审稿人的需求压倒性评论。在这项工作中,我们采用机制设计方法来提出改进同行评审过程的建议。我们提出了一个两阶段机制,将论文提交和审查过程联系在一起,同时激励高质量的审查和高质量的提交。在第一阶段,作者通过提交他们的论文以及代表他们对他们的论文进行评审的预期价值的出价来参与 VCG 拍卖以获取评审名额。在第二阶段,我们提出了一种新的预测市场式机制(H-DIPP),该机制建立在信息获取文献的最新工作基础上,它激励参与的评论者提供诚实和努力的评论。第一阶段拍卖的收入用于第二阶段,根据评论质量向评论者支付报酬。
更新日期:2021-09-03
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