‘Being good isn’t good enough’: gender discrimination in Italian academia

ABSTRACT

The article analyses the effect of gender in professors’ career advancement using data on the entire population of professors in the Italian university system, data on the National Scientific Qualification (NSQ) accreditation scheme, and data on scientific productivity (SciVal) for bibliometric scientific sectors. As NSQ accreditation is a prerequisite for career advancement in Italian universities, using this data makes it possible to rule out women’s reluctance to apply for promotions -candidate professors must apply for accreditation- as a mechanism for explaining the gender gap in academia. Our results show a relevant gender gap in career advancement that is not explained by gender differences in productivity (above the minimum level needed to obtain the accreditation). A structural gender bias also remains after controlling for available resources and for the percentage of female full professors in the academic scientific sector. The results contribute to the debate on the introduction of gender quotas.

KEYWORDS:

• Academic career
• discrimination
• gender
• scientific productivity
• Vertical segregation

Acknowledgement

We would like to thank Silvia Saviozzi, Patrizia Parisi and Giorgio Longo of our university’s Quality Evaluation Department for technical support in the initial stages of this research project.

Disclosure Statement

No potential conflict of interest was reported by the authors.

Ethical Statement

The authors declare the present work to be compliant with the Ethical Standards of Studies in Higher Education. They also declare no conflicts of interest. Ethics approval is not required for this paper.

Notes

1 ASN (Abilitazione Scientifica Nazionale).

2 See Section 2 for a detailed description of the Italian university system.

3 The number of reserved promotion procedures at each university cannot exceed the number of open competitions.

4 Source: 2015, 2016, 2017 Eurostat data from https://ec.europa.eu/eurostat/data/database.

5 The Moratti reform (Law 230/2005), in fact, introduced a degree of flexibilization in early career stages that has been confirmed and reinforced by the subsequent reforms (Bozzon, Murgia, and Villa 2017).

6 Mathematics and informatics (10 sub-sectors)s, Physics (8 sub-sectors), Chemistry (12 sub-sectors), Earth sciences (12 sub-sectors), Biology (19 sub-sectors), Medicine (50 sub-sectors), Agricultural and veterinary sciences (30 sub-sectors), Civil engineering and architecture (22 sub-sectors), Industrial and information engineering (42 sub-sectors), Antiquities, philology, literary studies, art history (67 sub-sectors), History, philosophy, pedagogy and psychology (34 sub-sectors), Law (21 sub-sectors), Economics and statistics (19 sub-sectors), Political and social sciences (14 sub-sectors).

7 The NSQ is currently in force in the Italian academic system. However the composition of the committees and the rules on the number of positive evaluations needed to obtain NSQ accreditation changed after the first two years of implementation. The threshold for obtaining the NSQ has gone from 4 positive votes out of 5–3 positive votes out of 5. Those reported in the text were the rules in force for the accreditation process for the individuals in our dataset.

8 EIGE (2017) gender balance implies a minimum objective of a 40% presence of the under-represented sex.

9 Data refer to the initial year of our observational period.

10 The web site is cercauniversita.cineca.it

11 Data on the entire Italian academic population are available since the year 2000, but information on each individual’s academic scientific sub-sector has been available only since 2001.

12 In some cases, individuals belonging to one academic scientific sub-sector were accredited in a different sub-sector within the same macro area. For this reason, we used the macro area (and not the sub-sector) to merge the two databases.

13 See for example https://www.lavoce.info/archives/18356/universita-professori-universitari-concorsi-abilitazione/ and https://www.roars.it/online/asn-2012-ecco-le-statistiche-finali-diverse-da-quelle-anvur/.

14 The h-index, proposed in 2005 by Jorge Hirsch, a physicist at the University of California, is a numerical indicator to measure a researcher’s productivity and how influential his/her research is. According to Hirsch’s definition, a scientist has index h if h of his/her N_p papers have at least h citations each, and the other (N_p−h) papers have no more than h citations each (Hirsh 2005).

15 SciVal is a modular integrated platform offered by Elsevier for the analysis of research results based on scientific production data. In particular, it provides information on more than 12,400 research institutions and their associated researchers from 230 nations worldwide.

16 The correlation between publications and citations is 0.87, while it is 0.65 between publications and the h-index.

17 Results are unchanged when the three indicators (h-index, number of publications and number of citations) are controlled for simultaneously.