The Miracle of Peer Review and Development in Science: An Agent-Based Model

TL;DR

This paper uses an agent-based model to analyze how peer review practices, journal impact factors, and reputation influence the quality of scientific publications and the sustainability of peer review.

Contribution

It introduces an agent-based simulation to explore the effects of editorial policies and reputation on scientific quality and peer review dynamics.

Findings

Reputation-based selection improves scientific quality.

Journal impact factors influence author and reviewer behavior.

Reciprocity among authors reduces review costs but doesn't enhance quality.

Abstract

It is not easy to rationalize how peer review, as the current grassroots of science, can work based on voluntary contributions of reviewers. There is no rationale to write impartial and thorough evaluations. Consequently, there is no risk in submitting low-quality work by authors. As a result, scientists face a social dilemma: if everyone acts according to his or her own self-interest, low scientific quality is produced. Still, in practice, reviewers as well as authors invest high effort in reviews and submissions. We examine how the increased relevance of public good benefits (journal impact factor), the editorial policy of handling incoming reviews, and the acceptance decisions that take into account reputational information can help the evolution of high-quality contributions from authors. High effort from the side of reviewers is problematic even if authors cooperate: reviewers are still best off by producing low-quality reviews, which does not hinder scientific development, just adds random noise and unnecessary costs to it. We show with agent-based simulations that tacit agreements between authors that are based on reciprocity might decrease these costs, but does not result in superior scientific quality. Our study underlines why certain self-emerged current practices, such as the increased importance of journal metrics, the reputation-based selection of reviewers, and the reputation bias in acceptance work efficiently for scientific development. Our results find no answers, however, how the system of peer review with impartial and thorough evaluations could be sustainable jointly with rapid scientific development.