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National peer-review research assessment exercises for the hard sciences can be a complete waste of money: the Italian case

Author

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  • Giovanni Abramo

    (National Research Council of Italy
    University of Rome “Tor Vergata”
    Università degli Studi di Roma “Tor Vergata”)

  • Tindaro Cicero

    (University of Rome “Tor Vergata”)

  • Ciriaco Andrea D’Angelo

    (University of Rome “Tor Vergata”)

Abstract

There has been ample demonstration that bibliometrics is superior to peer-review for national research assessment exercises in the hard sciences. In this paper we examine the Italian case, taking the 2001–2003 university performance rankings list based on bibliometrics as benchmark. We compare the accuracy of the first national evaluation exercise, conducted entirely by peer-review, to other rankings lists prepared at zero cost, based on indicators indirectly linked to performance or available on the Internet. The results show that, for the hard sciences, the costs of conducting the Italian evaluation of research institutions could have been completely avoided.

Suggested Citation

  • Giovanni Abramo & Tindaro Cicero & Ciriaco Andrea D’Angelo, 2013. "National peer-review research assessment exercises for the hard sciences can be a complete waste of money: the Italian case," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 311-324, April.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:1:d:10.1007_s11192-012-0875-6
    DOI: 10.1007/s11192-012-0875-6
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    References listed on IDEAS

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    1. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2008. "Assessment of sectoral aggregation distortion in research productivity measurements," Research Evaluation, Oxford University Press, vol. 17(2), pages 111-121, June.
    2. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2011. "Evaluating research: from informed peer review to bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 499-514, June.
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    7. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2011. "National research assessment exercises: a comparison of peer review and bibliometrics rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 929-941, December.
    8. Bornmann, Lutz & Leydesdorff, Loet, 2012. "Which are the best performing regions in information science in terms of highly cited papers? Some improvements of our previous mapping approaches," Journal of Informetrics, Elsevier, vol. 6(2), pages 336-345.
    9. Anthony F. J. Raan, 2006. "Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 67(3), pages 491-502, June.
    10. Franceschet, Massimo & Costantini, Antonio, 2011. "The first Italian research assessment exercise: A bibliometric perspective," Journal of Informetrics, Elsevier, vol. 5(2), pages 275-291.
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    Cited by:

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    3. Fionn Murtagh & Michael Orlov & Boris Mirkin, 2018. "Qualitative Judgement of Research Impact: Domain Taxonomy as a Fundamental Framework for Judgement of the Quality of Research," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 5-28, April.
    4. 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.
    5. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    6. Guo Chen & Lu Xiao & Chang-ping Hu & Xue-qin Zhao, 2015. "Identifying the research focus of Library and Information Science institutions in China with institution-specific keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 707-724, May.
    7. Zaida Chinchilla-Rodríguez & Grisel Zacca-González & Benjamín Vargas-Quesada & Félix Moya-Anegón, 2016. "Benchmarking scientific performance by decomposing leadership of Cuban and Latin American institutions in Public Health," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1239-1264, March.
    8. Bornmann, Lutz & Stefaner, Moritz & de Moya Anegón, Felix & Mutz, Rüdiger, 2014. "What is the effect of country-specific characteristics on the research performance of scientific institutions? Using multi-level statistical models to rank and map universities and research-focused in," Journal of Informetrics, Elsevier, vol. 8(3), pages 581-593.
    9. 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.
    10. 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.
    11. Sandra Rousseau & Ronald Rousseau, 2021. "Bibliometric Techniques And Their Use In Business And Economics Research," Journal of Economic Surveys, Wiley Blackwell, vol. 35(5), pages 1428-1451, December.

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