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Absolute and specific measures of research group excellence

Author

Listed:
  • O. Mryglod

    (Institute for Condensed Matter Physics of the NAS of Ukraine)

  • R. Kenna

    (Coventry University)

  • Yu. Holovatch

    (Institute for Condensed Matter Physics of the NAS of Ukraine)

  • B. Berche

    (Université de Lorraine, Campus de Nancy)

Abstract

A desirable goal of scientific management is to introduce, if it exists, a simple and reliable way to measure the scientific excellence of publicly funded research institutions and universities to serve as a basis for their ranking and financing. While citation-based indicators and metrics are easily accessible, they are far from being universally accepted as way to automate or inform evaluation processes or to replace evaluations based on peer review. Here we consider absolute measurements of research excellence at an amalgamated, institutional level and specific measures of research excellence as performance per head. Using biology research institutions in the UK as a test case, we examine the correlations between peer review-based and citation-based measures of research excellence on these two scales. We find that citation-based indicators are very highly correlated with peer-evaluated measures of group strength, but are poorly correlated with group quality. Thus, and almost paradoxically, our analysis indicates that citation counts could possibly form a basis for deciding on, how to fund research institutions, but they should not be used as a basis for ranking them in terms of quality.

Suggested Citation

  • O. Mryglod & R. Kenna & Yu. Holovatch & B. Berche, 2013. "Absolute and specific measures of research group excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 115-127, April.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:1:d:10.1007_s11192-012-0874-7
    DOI: 10.1007/s11192-012-0874-7
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    References listed on IDEAS

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    1. Péter Vinkler, 2001. "An attempt for defining some basic categories of scientometrics and classifying the indicators of evaluative scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 50(3), pages 539-544, March.
    2. Michael H. MacRoberts & Barbara R. MacRoberts, 1989. "Problems of citation analysis: A critical review," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 40(5), pages 342-349, September.
    3. Péter Vinkler, 2003. "Relations of relative scientometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 687-694, November.
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    Cited by:

    1. O. Mryglod & Yu. Holovatch & R. Kenna, 2022. "Big fish and small ponds: why the departmental h-index should not be used to rank universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3279-3292, June.
    2. Stephan B. Bruns & David I. Stern, 2016. "Research assessment using early citation information," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 917-935, August.
    3. R. Álvarez & E. Cahué & J. Clemente-Gallardo & A. Ferrer & D. Íñiguez & X. Mellado & A. Rivero & G. Ruiz & F. Sanz & E. Serrano & A. Tarancón & Y. Vergara, 2015. "Analysis of academic productivity based on Complex Networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 651-672, September.
    4. Paul Benneworth, 2015. "Between certainty and comprehensiveness in evaluating the societal impact of humanities research," CHEPS Working Papers 201502, University of Twente, Center for Higher Education Policy Studies (CHEPS).
    5. Uddin, Shahadat & Khan, Arif, 2016. "The impact of author-selected keywords on citation counts," Journal of Informetrics, Elsevier, vol. 10(4), pages 1166-1177.
    6. O. Mryglod & R. Kenna & Yu. Holovatch & B. Berche, 2015. "Predicting results of the research excellence framework using departmental h-index: revisited," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 1013-1017, September.
    7. Elio Atenógenes Villaseñor & Ricardo Arencibia-Jorge & Humberto Carrillo-Calvet, 2017. "Multiparametric characterization of scientometric performance profiles assisted by neural networks: a study of Mexican higher education institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 77-104, January.
    8. O. Mryglod & R. Kenna & Yu. Holovatch & B. Berche, 2015. "Predicting results of the Research Excellence Framework using departmental h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2165-2180, March.
    9. Hana Tomaskova & Martin Kopecky, 2020. "Specialization of Business Process Model and Notation Applications in Medicine—A Review," Data, MDPI, vol. 5(4), pages 1-42, October.
    10. Onodera, Natsuo, 2016. "Properties of an index of citation durability of an article," Journal of Informetrics, Elsevier, vol. 10(4), pages 981-1004.
    11. Liyin Zhang & Yuchen Qian & Chao Ma & Jiang Li, 2023. "Continued collaboration shortens the transition period of scientists who move to another institution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1765-1784, March.
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    13. Zhongyi Wang & Keying Wang & Jiyue Liu & Jing Huang & Haihua Chen, 2022. "Measuring the innovation of method knowledge elements in scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2803-2827, May.

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