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Opening the Black-Box of Peer Review: An Agent-Based Model of Scientist Behaviour

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Abstract

This paper investigates the impact of referee behaviour on the quality and efficiency of peer review. We focused on the importance of reciprocity motives in ensuring cooperation between all involved parties. We modelled peer review as a process based on knowledge asymmetries and subject to evaluation bias. We built various simulation scenarios in which we tested different interaction conditions and author and referee behaviour. We found that reciprocity cannot always have per se a positive effect on the quality of peer review, as it may tend to increase evaluation bias. It can have a positive effect only when reciprocity motives are inspired by disinterested standards of fairness.

Suggested Citation

  • Flaminio Squazzoni & Claudio Gandelli, 2013. "Opening the Black-Box of Peer Review: An Agent-Based Model of Scientist Behaviour," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(2), pages 1-3.
    • Handle: RePEc:jas:jasssj:2012-72-3
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    Citations

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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. 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.
    4. Sun, Zhuanlan, 2024. "Textual features of peer review predict top-cited papers: An interpretable machine learning perspective," Journal of Informetrics, Elsevier, vol. 18(2).
    5. Feliciani, Thomas & Morreau, Michael & Luo, Junwen & Lucas, Pablo & Shankar, Kalpana, 2022. "Designing grant-review panels for better funding decisions: Lessons from an empirically calibrated simulation model," Research Policy, Elsevier, vol. 51(4).
    6. 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.
    7. J. A. Garcia & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2021. "The interplay between the reviewer’s incentives and the journal’s quality standard," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3041-3061, April.
    8. J. A. Garcia & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2020. "The author–reviewer game," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2409-2431, September.
    9. ederico Bianchi & Flaminio Squazzoni, 2022. "Can transparency undermine peer review? A simulation model of scientist behavior under open peer review [Reviewing Peer Review]," Science and Public Policy, Oxford University Press, vol. 49(5), pages 791-800.
    10. 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.
    11. 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).
    12. 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.
    13. 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.

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