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Refrain from adopting the combination of citation and journal metrics to grade publications, as used in the Italian national research assessment exercise (VQR 2011–2014)

Author

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  • Giovanni Abramo

    (National Research Council of Italy)

  • Ciriaco Andrea D’Angelo

    (National Research Council of Italy
    University of Rome “Tor Vergata”)

Abstract

The prediction of the long-term impact of a scientific article is challenging task, addressed by the bibliometrician through resorting to a proxy whose reliability increases with the breadth of the citation window. In the national research assessment exercises using metrics the citation window is necessarily short, but in some cases is sufficient to advise the use of simple citations. For the Italian VQR 2011–2014, the choice was instead made to adopt a linear weighted combination of citations and journal metric percentiles, with weights differentiated by discipline and year. Given the strategic importance of the exercise, whose results inform the allocation of a significant share of resources for the national academic system, we examined whether the predictive power of the proposed indicator is stronger than the simple citation count. The results show the opposite, for all discipline in the sciences and a citation window above 2 years.

Suggested Citation

  • Giovanni Abramo & Ciriaco Andrea D’Angelo, 2016. "Refrain from adopting the combination of citation and journal metrics to grade publications, as used in the Italian national research assessment exercise (VQR 2011–2014)," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2053-2065, December.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:3:d:10.1007_s11192-016-2153-5
    DOI: 10.1007/s11192-016-2153-5
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    References listed on IDEAS

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    Cited by:

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    4. Mike Thelwall & Kayvan Kousha & Emma Stuart & Meiko Makita & Mahshid Abdoli & Paul Wilson & Jonathan Levitt, 2023. "In which fields are citations indicators of research quality?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(8), pages 941-953, August.
    5. Francesco Giovanni Avallone & Alberto Quagli & Paola Ramassa, 2022. "Interdisciplinary research by accounting scholars: An exploratory study," FINANCIAL REPORTING, FrancoAngeli Editore, vol. 2022(2), pages 5-34.
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    7. Camil Demetrescu & Andrea Ribichini & Marco Schaerf, 2020. "Are Italian research assessment exercises size-biased?," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 533-549, October.
    8. Alberto Baccini & Lucio Barabesi & Giuseppe De Nicolao, 2020. "On the agreement between bibliometrics and peer review: Evidence from the Italian research assessment exercises," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-28, November.
    9. Cappelletti-Montano, Beniamino & Columbu, Silvia & Montaldo, Stefano & Musio, Monica, 2022. "Interpreting the outcomes of research assessments: A geometrical approach," Journal of Informetrics, Elsevier, vol. 16(1).
    10. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Felici, Giovanni, 2019. "Predicting publication long-term impact through a combination of early citations and journal impact factor," Journal of Informetrics, Elsevier, vol. 13(1), pages 32-49.
    11. Jiayu Li, 2023. "Publications in Educational Research Journals from Singapore, Japan, and South Korea (2008–2017): A Bibliometric Analysis," SAGE Open, , vol. 13(4), pages 21582440231, December.
    12. Giovanni Abramo & Ciriaco Andrea D’Angelo & Emanuela Reale, 2019. "Peer review versus bibliometrics: Which method better predicts the scholarly impact of publications?," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 537-554, October.
    13. Gauffriau, Marianne, 2017. "A categorization of arguments for counting methods for publication and citation indicators," Journal of Informetrics, Elsevier, vol. 11(3), pages 672-684.
    14. Vasilios D. Kosteas, 2018. "Predicting long-run citation counts for articles in top economics journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1395-1412, June.
    15. Demetrescu, Camil & Lupia, Francesco & Mendicelli, Angelo & Ribichini, Andrea & Scarcello, Francesco & Schaerf, Marco, 2019. "On the Shapley value and its application to the Italian VQR research assessment exercise," Journal of Informetrics, Elsevier, vol. 13(1), pages 87-104.
    16. Abramo, Giovanni, 2018. "Revisiting the scientometric conceptualization of impact and its measurement," Journal of Informetrics, Elsevier, vol. 12(3), pages 590-597.

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