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

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  • Simone Righi
  • Karoly Takacs

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 lowquality 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 scientifi9c development.

Suggested Citation

  • Simone Righi & Karoly Takacs, 2016. "The Miracle of Peer Review and Development inScience: An Agent-Based Model," Center for the Analysis of Public Policies (CAPP) 0144, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
  • Handle: RePEc:mod:cappmo:0144
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    1. Squazzoni, Flaminio & Bravo, Giangiacomo & Takács, Károly, 2013. "Does incentive provision increase the quality of peer review? An experimental study," Research Policy, Elsevier, vol. 42(1), pages 287-294.
    2. Pawel Sobkowicz, 2015. "Innovation Suppression and Clique Evolution in Peer-Review-Based, Competitive Research Funding Systems: An Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-13.
    3. Mario Paolucci & Jaime Simão Sichman, 2014. "Reputation to understand society," Computational and Mathematical Organization Theory, Springer, vol. 20(2), pages 211-217, June.
    4. Mario Paolucci & Francisco Grimaldo, 2014. "Mechanism change in a simulation of peer review: from junk support to elitism," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 663-688, June.
    5. N. Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, , vol. 2(2), pages 91-105, June.
    6. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    7. Michail Kovanis & Raphaël Porcher & Philippe Ravaud & Ludovic Trinquart, 2016. "Complex systems approach to scientific publication and peer-review system: development of an agent-based model calibrated with empirical journal data," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 695-715, February.
    8. Wang, Jian, 2014. "Unpacking the Matthew effect in citations," Journal of Informetrics, Elsevier, vol. 8(2), pages 329-339.
    9. Squazzoni, Flaminio & Gandelli, Claudio, 2012. "Saint Matthew strikes again: An agent-based model of peer review and the scientific community structure," Journal of Informetrics, Elsevier, vol. 6(2), pages 265-275.
    10. Flaminio Squazzoni & Károly Takács, 2011. "Social Simulation That 'Peers into Peer Review'," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-3.
    11. Raj Chetty & Emmanuel Saez & Laszlo Sandor, 2014. "What Policies Increase Prosocial Behavior? An Experiment with Referees at the Journal of Public Economics," Journal of Economic Perspectives, American Economic Association, vol. 28(3), pages 169-188, Summer.
    12. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    13. Martin A. Nowak & Karl Sigmund, 2005. "Evolution of indirect reciprocity," Nature, Nature, vol. 437(7063), pages 1291-1298, October.
    14. Marco Seeber & Alberto Bacchelli, 2017. "Does single blind peer review hinder newcomers?," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 567-585, October.
    15. Day, Theodore Eugene, 2015. "The big consequences of small biases: A simulation of peer review," Research Policy, Elsevier, vol. 44(6), pages 1266-1270.
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    Cited by:

    1. Bravo, Giangiacomo & Farjam, Mike & Grimaldo Moreno, Francisco & Birukou, Aliaksandr & Squazzoni, Flaminio, 2018. "Hidden connections: Network effects on editorial decisions in four computer science journals," Journal of Informetrics, Elsevier, vol. 12(1), pages 101-112.
    2. Michail Kovanis & Ludovic Trinquart & Philippe Ravaud & Raphaël Porcher, 2017. "Evaluating alternative systems of peer review: a large-scale agent-based modelling approach to scientific publication," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 651-671, October.
    3. Thomas Feliciani & Junwen Luo & Lai Ma & Pablo Lucas & Flaminio Squazzoni & Ana Marušić & Kalpana Shankar, 2019. "A scoping review of simulation models of peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 555-594, October.
    4. Francisco Grimaldo & Mario Paolucci & Jordi Sabater-Mir, 2018. "Reputation or peer review? The role of outliers," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1421-1438, September.
    5. Zhao, Zhi-Dan & Chen, Jiahao & Lu, Yichuan & Zhao, Na & Jiang, Dazhi & Wang, Bing-Hong, 2021. "Dynamic patterns of open review process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    6. Thomas Feliciani & Ramanathan Moorthy & Pablo Lucas & Kalpana Shankar, 2020. "Grade Language Heterogeneity in Simulation Models of Peer Review," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(3), pages 1-8.
    7. Guy Madison & Knut Sundell, 2022. "Numbers of publications and citations for researchers in fields pertinent to the social services: a comparison of peer-reviewed journal publications across six disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 6029-6046, October.
    8. Zhang, Guangyao & Xu, Shenmeng & Sun, Yao & Jiang, Chunlin & Wang, Xianwen, 2022. "Understanding the peer review endeavor in scientific publishing," Journal of Informetrics, Elsevier, vol. 16(2).
    9. Federico Bianchi & Francisco Grimaldo & Giangiacomo Bravo & Flaminio Squazzoni, 2018. "The peer review game: an agent-based model of scientists facing resource constraints and institutional pressures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1401-1420, September.
    10. Monica Aniela Zaharie & Marco Seeber, 2018. "Are non-monetary rewards effective in attracting peer reviewers? A natural experiment," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1587-1609, December.

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    More about this item

    Keywords

    peer review; evolution of cooperation; reputation; agent based model.;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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