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Research-driven classification and ranking in higher education: an empirical appraisal of a Romanian policy experience

Author

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  • Gabriel-Alexandru Vîiu

    (National School of Political and Administrative Studies)

  • Mihai Păunescu

    (National School of Political and Administrative Studies)

  • Adrian Miroiu

    (National School of Political and Administrative Studies)

Abstract

In this paper we investigate the problem of university classification and its relation to ranking practices in the policy context of an official evaluation of Romanian higher education institutions and their study programs. We first discuss the importance of research in the government-endorsed assessment process and analyze the evaluation methodology and the results it produced. Based on official documents and data we show that the Romanian classification of universities was implicitly hierarchical in its conception and therefore also produced hierarchical results due to its close association with the ranking of study programs and its heavy reliance on research outputs. Then, using a distinct dataset on the research performance of 1385 faculty members working in the fields of political science, sociology and marketing we further explore the differences between university categories. We find that our alternative assessment of research productivity—measured with the aid of Hirsch’s (Proc Natl Acad Sci 102(46):16569–16572, 2005) h-index and with Egghe’s (Scientometrics 69(1):131–152, 2006) g-index—only provides empirical support for a dichotomous classification of Romanian institutions.

Suggested Citation

  • Gabriel-Alexandru Vîiu & Mihai Păunescu & Adrian Miroiu, 2016. "Research-driven classification and ranking in higher education: an empirical appraisal of a Romanian policy experience," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 785-805, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1860-2
    DOI: 10.1007/s11192-016-1860-2
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    References listed on IDEAS

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    1. Anne-Wil Harzing & Satu Alakangas & David Adams, 2014. "hIa: an individual annual h-index to accommodate disciplinary and career length differences," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 811-821, June.
    2. Bornmann, Lutz & Mutz, Rüdiger & Hug, Sven E. & Daniel, Hans-Dieter, 2011. "A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants," Journal of Informetrics, Elsevier, vol. 5(3), pages 346-359.
    3. Pedro Albarrán & Juan A. Crespo & Ignacio Ortuño & Javier Ruiz-Castillo, 2011. "The skewness of science in 219 sub-fields and a number of aggregates," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 385-397, August.
    4. Jean-Charles Billaut & Denis Bouyssou & Philippe Vincke, 2010. "Should you believe in the Shanghai ranking?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 237-263, July.
    5. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    6. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
    7. Aldo Geuna, 2001. "The Changing Rationale for European University Research Funding: Are There Negative Unintended Consequences?," Journal of Economic Issues, Taylor & Francis Journals, vol. 35(3), pages 607-632, September.
    8. Kaur, Jasleen & Radicchi, Filippo & Menczer, Filippo, 2013. "Universality of scholarly impact metrics," Journal of Informetrics, Elsevier, vol. 7(4), pages 924-932.
    9. Costas, Rodrigo & Bordons, María, 2007. "The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level," Journal of Informetrics, Elsevier, vol. 1(3), pages 193-203.
    10. Jamil Salmi & Alenoush Saroyan, 2007. "League Tables as Policy Instruments: Uses and Misuses," Higher Education Management and Policy, OECD Publishing, vol. 19(2), pages 1-38.
    11. Ortega, José Luis & López-Romero, Elena & Fernández, Inés, 2011. "Multivariate approach to classify research institutes according to their outputs: The case of the CSIC's institutes," Journal of Informetrics, Elsevier, vol. 5(3), pages 323-332.
    12. repec:dau:papers:123456789/2947 is not listed on IDEAS
    13. Ying Cheng & Nian Cai Liu, 2006. "A first approach to the classification of the top 500 world universities by their disciplinary characteristics using scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 135-150, July.
    14. Per O. Seglen, 1992. "The skewness of science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 628-638, October.
    15. Jamil Salmi, 2009. "The Challenge of Establishing World-Class Universities," World Bank Publications - Books, The World Bank Group, number 2600.
    16. Michael Schreiber, 2008. "An empirical investigation of the g‐index for 26 physicists in comparison with the h‐index, the A‐index, and the R‐index," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(9), pages 1513-1522, July.
    17. Hicks, Diana, 2012. "Performance-based university research funding systems," Research Policy, Elsevier, vol. 41(2), pages 251-261.
    18. J.A. García & Rosa Rodríguez-Sánchez & J. Fdez-Valdivia & N. Robinson-García & D. Torres-Salinas, 2012. "Mapping academic institutions according to their journal publication profile: Spanish universities as a case study," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2328-2340, November.
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    Cited by:

    1. Rachida Aïssaoui & J. Michael Geringer & Grigorios Livanis, 2020. "International Collaboration and European Contributions to International Business Research," Management International Review, Springer, vol. 60(6), pages 827-868, December.
    2. Claudiu Vasile Kifor & Ana Maria Benedek & Ioan Sîrbu & Roxana Florența Săvescu, 2023. "Institutional drivers of research productivity: a canonical multivariate analysis of Romanian public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2233-2258, April.
    3. Gabriel-Alexandru Vîiu & Mihai Păunescu, 2021. "The citation impact of articles from which authors gained monetary rewards based on journal metrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4941-4974, June.
    4. Claudiu Vasile Kifor & Daniel Teodorescu & Tudorel Andrei & Roxana Săvescu, 2021. "Research Production and International Visibility in Higher Education: The Evolution of Romanian Universities from 2011 to 2019," Sustainability, MDPI, vol. 13(23), pages 1-18, December.

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