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Quantitative analysis of the Italian National Scientific Qualification

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  • Marzolla, Moreno

Abstract

The Italian National Scientific Qualification (ASN) was introduced in 2010 as part of a major reform of the national university system. Under the new regulation, the scientific qualification for a specific role (associate or full professor) and field of study is required to apply for a permanent professor position. The ASN is peculiar since it makes use of bibliometric indicators with associated thresholds as one of the parameters used to assess applicants. The first round of the ASN received 59,149 applications, and the results have been made publicly available for a short period of time, including the values of the quantitative indicators for each applicant. The availability of this wealth of information provides an opportunity to draw a fairly detailed picture of a nation-wide evaluation exercise, and to study the impact of the bibliometric indicators on the qualification results. In this paper, we provide a first account of the Italian National Scientific Qualification from a quantitative point of view. We show that significant differences exist among scientific disciplines, in particular with respect to the fraction of qualified applicants, that cannot be easily explained. Furthermore, we describe some issues related to the definition and use of the bibliometric indicators and the corresponding thresholds. Our analysis aims at drawing attention to potential problems that should be addressed by decision-makers in future rounds of the ASN.

Suggested Citation

  • Marzolla, Moreno, 2015. "Quantitative analysis of the Italian National Scientific Qualification," Journal of Informetrics, Elsevier, vol. 9(2), pages 285-316.
    • Handle: RePEc:eee:infome:v:9:y:2015:i:2:p:285-316
    DOI: 10.1016/j.joi.2015.02.006
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    References listed on IDEAS

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    1. 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.
    2. Antonis Sidiropoulos & Dimitrios Katsaros & Yannis Manolopoulos, 2007. "Generalized Hirsch h-index for disclosing latent facts in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(2), pages 253-280, August.
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2011. "Research productivity: Are higher academic ranks more productive than lower ones?," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 915-928, September.
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    Cited by:

    1. Maria Cristiana Martini & Elvira Pelle & Francesco Poggi & Andrea Sciandra, 2022. "The role of citation networks to explain academic promotions: an empirical analysis of the Italian national scientific qualification," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 5633-5659, October.
    2. Giovanni Abramo & Ciriaco D’Angelo, 2015. "An assessment of the first “scientific habilitation” for university appointments in Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 32(3), pages 329-357, December.
    3. Camil Demetrescu & Irene Finocchi & Andrea Ribichini & Marco Schaerf, 2020. "On bibliometrics in academic promotions: a case study in computer science and engineering in Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2207-2228, September.
    4. Marzolla, Moreno, 2016. "Assessing evaluation procedures for individual researchers: The case of the Italian National Scientific Qualification," Journal of Informetrics, Elsevier, vol. 10(2), pages 408-438.
    5. Silvio Peroni & Paolo Ciancarini & Aldo Gangemi & Andrea Giovanni Nuzzolese & Francesco Poggi & Valentina Presutti, 2020. "The practice of self-citations: a longitudinal study," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 253-282, April.

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