The objective of science is to advance knowledge, primarily in two interlinked ways: circulating ideas, and defending or criticizing the ideas of others. Peer review acts as the gatekeeper to these mechanisms. Given the increasing concern surrounding the reproducibility of much published research1, it is critical to understand whether peer review is intrinsically susceptible to failure, or whether other extrinsic factors are responsible that distort scientists’ decisions. Here we show that even when scientists are motivated to promote the truth, their behaviour may be influenced, and even dominated, by information gleaned from their peers’ behaviour, rather than by their personal dispositions. This phenomenon, known as herding, subjects the scientific community to an inherent risk of converging on an incorrect answer and raises the possibility that, under certain conditions, science may not be self-correcting. We further demonstrate that exercising some subjectivity in reviewer decisions, which serves to curb the herding process, can be beneficial for the scientific community in processing available information to estimate truth more accurately. By examining the impact of different models of reviewer decisions on the dynamic process of publication, and thereby on eventual aggregation of knowledge, we provide a new perspective on the ongoing discussion of how the peer-review process may be improved.
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This research was supported by an Economics and Social Research Council UK PhD studentship to M.W.P. M.R.M. is a member of the UK Centre for Tobacco and Alcohol Studies, a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, and the National Institute for Health Research, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. The authors are grateful to S. Murphy for her assistance in coding the meta-analysis study abstracts, and to A. Bird and G. Huxley for their comments on earlier drafts of this manuscript.
This file contains Supplementary Sections 1-4. Section 1 contains the computer program used to find the numerical results presented in the main article. Section 2 presents an example of de-herding occurring in the M1 model. Section 3 discusses the effect of relaxing the common knowledge assumption of rejections, and analyses alternative models for comparison and Section 4 considers the case that the scientists are motivated to simply publish (regardless of the truthfulness of the defended theme), and shows that immediate and complete herding may occur.