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Mechanism change in a simulation of peer review: from junk support to elitism

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  • Mario Paolucci

    (Italian National Research Council)

  • Francisco Grimaldo

    (Universitat de València)

Abstract

Peer review works as the hinge of the scientific process, mediating between research and the awareness/acceptance of its results. While it might seem obvious that science would regulate itself scientifically, the consensus on peer review is eroding; a deeper understanding of its workings and potential alternatives is sorely needed. Employing a theoretical approach supported by agent-based simulation, we examined computational models of peer review, performing what we propose to call redesign, that is, the replication of simulations using different mechanisms. Here, we show that we are able to obtain the high sensitivity to rational cheating that is present in literature. In addition, we also show how this result appears to be fragile against small variations in mechanisms. Therefore, we argue that exploration of the parameter space is not enough if we want to support theoretical statements with simulation, and that exploration at the level of mechanisms is needed. These findings also support prudence in the application of simulation results based on single mechanisms, and endorse the use of complex agent platforms that encourage experimentation of diverse mechanisms.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:99:y:2014:i:3:d:10.1007_s11192-014-1239-1
    DOI: 10.1007/s11192-014-1239-1
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    Cited by:

    1. 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.
    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. 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.
    5. 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.
    6. Simone Righi & Károly Takács, 2017. "The miracle of peer review and development in science: an agent-based model," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 587-607, 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. 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.

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