Reputation or peer review? The role of outliers
Francisco Grimaldo (),
Mario Paolucci () and
Jordi Sabater-Mir ()
Additional contact information
Francisco Grimaldo: Universitat de València
Mario Paolucci: Italian National Research Council
Jordi Sabater-Mir: Spanish National Research Council
Scientometrics, 2018, vol. 116, issue 3, No 2, 1438 pages
Abstract:
Abstract We present an agent-based model of paper publication and consumption that allows to study the effect of two different evaluation mechanisms, peer review and reputation, on the quality of the manuscripts accessed by a scientific community. The model was empirically calibrated on two data sets, mono- and multi-disciplinary. Our results point out that disciplinary settings differ in the rapidity with which they deal with extreme events—papers that have an extremely high quality, that we call outliers. In the mono-disciplinary case, reputation is better than traditional peer review to optimize the quality of papers read by researchers. In the multi-disciplinary case, if the quality landscape is relatively flat, a reputation system also performs better. In the presence of outliers, peer review is more effective. Our simulation suggests that a reputation system could perform better than peer review as a scientific information filter for quality except when research is multi-disciplinary and in a field where outliers exist.
Keywords: Peer review; Reputation; Agent-based simulation; Multi-disciplinary science; Outliers; Information filter (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s11192-018-2826-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:116:y:2018:i:3:d:10.1007_s11192-018-2826-3
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192
DOI: 10.1007/s11192-018-2826-3
Access Statistics for this article
Scientometrics is currently edited by Wolfgang Glänzel
More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().