| 1. |
- Bianchi, Federico, et al.
(författare)
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The peer review game : an agent-based model of scientists facing resource constraints and institutional pressures
- 2018
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Ingår i: Scientometrics. - : Springer. - 0138-9130 .- 1588-2861. ; 116:3, s. 1401-1420
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Tidskriftsartikel (refereegranskat)abstract
- This paper looks at peer review as a cooperation dilemma through a game-theory framework. We built an agent-based model to estimate how much the quality of peer review is influenced by different resource allocation strategies followed by scientists dealing with multiple tasks, i.e., publishing and reviewing. We assumed that scientists were sensitive to acceptance or rejection of their manuscripts and the fairness of peer review to which they were exposed before reviewing. We also assumed that they could be realistic or excessively over-confident about the quality of their manuscripts when reviewing. Furthermore, we assumed they could be sensitive to competitive pressures provided by the institutional context in which they were embedded. Results showed that the bias and quality of publications greatly depend on reviewer motivations but also that context pressures can have a negative effect. However, while excessive competition can be detrimental to minimising publication bias, a certain level of competition is instrumental to ensure the high quality of publication especially when scientists accept reviewing for reciprocity motives.
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| 2. |
- Bravo, Giangiacomo, et al.
(författare)
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Hidden connections : Network effects on editorial decisions in four computer science journals
- 2018
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Ingår i: Journal of Informetrics. - : Elsevier. - 1751-1577 .- 1875-5879. ; 12:1, s. 101-112
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims to examine the influence of authors’ reputation on editorial bias in scholarly journals. By looking at eight years of editorial decisions in four computer science journals, including 7179 observations on 2913 submissions, we reconstructed author/referee-submission networks. For each submission, we looked at reviewer scores and estimated the reputation of submission authors by means of their network degree. By training a Bayesian network, we estimated the potential effect of scientist reputation on editorial decisions. Results showed that more reputed authors were less likely to be rejected by editors when they submitted papers receiving negative reviews. Although these four journals were comparable for scope and areas, we found certain journal specificities in their editorial process. Our findings suggest ways to examine the editorial process in relatively similar journals without recurring to in-depth individual data, which are rarely available from scholarly journals.
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