Peer Review versus Bibliometrics: Which Method Better Predicts the Scholarly Impact of Publications?
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Bibliometric indicators were generally shown to be positively correlated with peer-review evaluations.
“Although bibliometric indicators were generally shown to be positively correlated with peer-review evaluations”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [276]
Peer review has its own characteristic biases and limitations, which is one reason peer review has been increasingly replaced with bibliometric measures of impact.
“peer-reviewing has its own characteristic biases and limitations, which is one of the reasons why, nowadays, peer-review has been increasingly extensively replaced with bibliometric measures of impact [3,44,276].”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [276]
Correlations between metrics and expert judgements vary greatly across disciplines, application contexts, and between metrics used.
“it was also observed that the correlations between metrics and expert judgements vary greatly across disciplines, application contexts, and between metrics used [44,276,280,282].”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [276]
These conclusions cannot be extrapolated as a general tendency because most comparisons had limitations and differed in design.
“However, these conclusions cannot be extrapolated as a general tendency because most of these comparisons had certain limitations and differed in their design [44,276].”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [276]
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References 60 · Cited by 50
Research works printed but not linked: 11
- Alfò, M., Benedetto, S., Malgarini, M., & Scipione, S. (2017). On the use of bibliometric information for assessing articles quality: an analysis based on the third Italian research evaluation exercise. 2017 STI Conference . Paris.
- Baccini, A., Barabesi, L., & De Nicolao, G. (2018). The Holy Grail and the bad sampling: a test for the homogeneity of missing proportions for evaluating the agreement between peer review and bibliometrics in the Italian research assessment exercises. arXiv:1810.12430v1. · arXiv
- Cole, J. R., & Cole, S. (1973). Social Stratification in Science . Chicago/London: University of Chicago Press.
- Garfield, E. (1979). Citation indexing-its theory and application in science, technology, and humanities . New York, NY: Wiley.
- Glänzel, W. (2008). Seven myths in bibliometrics. About facts and fiction in quantitative science studies. Kretschmer & F. Havemann (eds): Proceedings of WIS Fourth International Conference on Webometrics, Informetrics and Scientometrics & Ninth COLLNET Meeting , Berlin, Germany.
- Kreiman, G., & Maunsell, J. H. R. (2011). Nine criteria for a measure of scientific output. Frontiers in Computational Neuroscience, 5(48), 11.
- Lin, L.I-K. (2000). Erratum: A note on the concordance correlation coefficient (biometrics (1989) (214)). Biometrics , 56(1), 324-325.
- Merton, R. K. , ( 1973 ). Priorities in scientific discovery . In R. K. Merton (Ed.), The sociology of science: Theoretical and empirical investigations (pp. 286 -324 ). Chicago : University of Chicago Press.
- Moxam, H., Anderson, J. (1992). Peer review. A view from the inside. Science and Technology Policy, 5(1), 7-15.
- Oppenheim, C., & Norris, M. (2003). Citation counts and the research assessment exercise V: archaeology and the 2001 RAE. Journal of Documentation , 56(6), pp. 709-730.
- van Raan, A.F.J. (2004). Sleeping beauties in science. Scientometrics , 59(3), 461-466.
- Authors
- Abramo, G., D’Angelo, C. A., & Reale, E.
- Affiliations
- National Research Council (IT)
- University of Rome Tor Vergata (IT)
- Research Institute on Sustainable Economic Growth (IT)
- Corresponding author
- Abramo, Giovanni
- Venue
- Scientometrics
- Published
- 2019-07-11
- Volume
- 121
- Issue
- 1
- Pages
- 537-554
- ISSN
- 0138-9130 (ISSN-L)
- 1588-2861
- OpenAlex
- W2957599721
- Cited by
- 50
- References
- 60
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 11 · 2023: 6 · 2022: 7 · 2021: 7 · 2020: 6 · 2019: 2
- FWCI
- 3.69
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Scientometrics (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Cineca Institutional Research Information System (Tor Vergata University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Physical Sciences › Computer Science › Information Systems › Web visibility and informetrics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- peer review, bibliometric analysis, scholarly impact, citation metrics, h-index, research evaluation, Web of Science, disciplinary differences
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