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An evolutionary explanation of assassins and zealots in peer review

Author

Listed:
  • Jorge Chamorro-Padial

    (Universidad de Granada)

  • Rosa Rodriguez-Sánchez

    (Universidad de Granada)

  • J. Fdez-Valdivia

    (Universidad de Granada)

  • J. A. Garcia

    (Universidad de Granada)

Abstract

The peer review system aims to be effective in separating unacceptable from acceptable manuscripts. However, a reviewer can distinguish them or not. If reviewers distinguish unacceptable from acceptable manuscripts they use a fine partition of categories. But, if reviewers do not distinguish them they use a coarse partition in the evaluation of manuscripts. Most reviewers learned how to evaluate a manuscript from good and bad experiences, and they have been characterized as zealots (who uncritically favor a manuscript), assassins (who advise rejection much more frequently than the norm), and mainstream referees. In this paper we use the quasi-species model to describe the evolution of recommendation profiles in peer review. A recommendation profile is composed of a reviewer recommendation for each manuscript category under a particular categorization of manuscripts (fine or coarse). We see the reviewer mind as being built up with recommendation profiles. Assassins, zealots and mainstream reviewers are “ecologically” interrelated species whose progeny tend to mutate through errors made in the process of reviewer training. We define the recommendation profile as replicator, and selection arises because different types of recommendation profiles tend to replicate at different rates. Our results help to explain why assassins and zealots evolutionary appear in peer review because of the evolutionary success of reviewers who do not distinguish acceptable and unacceptable manuscripts.

Suggested Citation

  • Jorge Chamorro-Padial & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia & J. A. Garcia, 2019. "An evolutionary explanation of assassins and zealots in peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1373-1385, September.
    • Handle: RePEc:spr:scient:v:120:y:2019:i:3:d:10.1007_s11192-019-03171-3
    DOI: 10.1007/s11192-019-03171-3
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    References listed on IDEAS

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    1. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
    2. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2016. "Why the referees’ reports I receive as an editor are so much better than the reports I receive as an author?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 967-986, March.
    3. Rodriguez-Sánchez, Rosa & García, J.A. & Fdez-Valdivia, J., 2016. "Evolutionary games between authors and their editors," Applied Mathematics and Computation, Elsevier, vol. 273(C), pages 645-655.
    4. Jose A. García & Rosa Rodriguez-Sánchez & Joaquín Fdez-Valdivia, 2015. "Adverse selection of reviewers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(6), pages 1252-1262, June.
    5. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
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    Cited by:

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    2. Grażyna Wieczorkowska & Katarzyna Kowalczyk, 2021. "Ensuring Sustainable Evaluation: How to Improve Quality of Evaluating Grant Proposals?," Sustainability, MDPI, vol. 13(5), pages 1-11, March.

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