Accelerating the pace of discovery by changing the peer review algorithm
Stefano Allesina

TL;DR
This paper introduces an agent-based simulation model to evaluate and compare different peer review systems, demonstrating that journal bidding can significantly improve review efficiency, publication quality, and reviewer effort.
Contribution
The paper presents a novel simulation framework for modeling peer review, allowing quantitative testing of different review system designs, including a new journal bidding approach.
Findings
Journal bidding speeds up review process
Authors publish more in better journals
Reviewer effort is more efficiently allocated
Abstract
The number of scientific publications is constantly rising, increasing the strain on the review process. The number of submissions is actually higher, as each manuscript is often reviewed several times before publication. To face the deluge of submissions, top journals reject a considerable fraction of manuscripts without review, potentially declining manuscripts with merit. The situation is frustrating for authors, reviewers and editors alike. Recently, several editors wrote about the ``tragedy of the reviewer commons', advocating for urgent corrections to the system. Almost every scientist has ideas on how to improve the system, but it is very difficult, if not impossible, to perform experiments to test which measures would be most effective. Surprisingly, relatively few attempts have been made to model peer review. Here I implement a simulation framework in which ideas on peer review…
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Taxonomy
TopicsEvolutionary Game Theory and Cooperation · Scientific Computing and Data Management · Evolution and Genetic Dynamics
