Evaluation Practices and Effects of Indicator Use—A Literature Review
Abstract
This review of the international literature on evaluation systems, evaluation practices, and metrics (mis)uses was written as part of a larger review commissioned by the Higher Education Funding Council for England (HEFCE) to inform their independent assessment of the role of metrics in research evaluation (2014–5). The literature on evaluation systems, practices, and effects of indicator uses is extremely heterogeneous: it comprises hundreds of sources published in different media, spread over disciplines, and with considerable variation in the nature of the evidence. A condensation of the state-of-the-art in relevant research is therefore highly timely. Our review presents the main strands in the literature, with a focus on empirical materials about possible effects of evaluation exercises, ‘gaming’ of indicators, and strategic responses by scientific communities and others to requirements in research assessments. In order to increase visibility and availability, an adapted and updated review is presented here as a stand-alone—after authorization by HEFCE.
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Only a minority of stakeholders employing bibliometric indicators are adequately familiar with their meaning and appropriate use.
“Yet, only a minority of stakeholders employing bibliometric indicators are adequately familiar with their meaning and appropriate use [2,4,5,7].”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [7]
The 'publish or perish' attitude stimulates productivity of researchers but creates a bias towards quantity, often overlooking quality.
“this 'publish or perish' attitude, on the one hand, stimulates the productivity of researchers, but, on the other, creates a bias towards quantity, often overlooking quality [2,3,6-8,44,81,163,260,263,284-288].”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [7]
Publication data and citation metrics continue to play the most important role in research assessments worldwide, so indicator-based research assessments remain at the center of global debate about their validity and influence.
“because publication data and citation metrics continue to play the most important role in research assessments worldwide, indicator-based research assessments also remain at the center of the global debate, not only about their validity, but also about their influence on research activities, scientific output, and its quality [1,5-7,44,260,265,289].”
From Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World (2021) · cites this paper as [7]
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- Authors
- Rijcke, S. D., Wouters, P. F., Rushforth, A. D., Franssen, T. P., & Hammarfelt, B.
- Affiliations
- Leiden University (NL)
- Corresponding author
- Rijcke, Sarah de
- Venue
- Research Evaluation
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-12-29
- Volume
- 25
- Issue
- 2
- Pages
- 161-169
- ISSN
- 0958-2029 (ISSN-L)
- 1471-5449
- OpenAlex
- W2235214564
- Cited by
- 467
- References
- 117
- Citations by year
- 2026: 41 · 2025: 35 · 2024: 52 · 2023: 43 · 2022: 58 · 2021: 56 · 2020: 56 · 2019: 44 · 2018: 41 · 2017: 28 · 2016: 12 · 2015: 1
- FWCI
- 4.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Research Evaluation (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Social Sciences › Political Science and International Relations › Higher Education Governance and Development
- Social Sciences › Decision Sciences › Information Systems and Management › Research, Science, and Academia
- Keywords
- evaluation metrics, assessment practices, evaluation system, research evaluation, higher education research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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