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The north–south divide in the Italian higher education system

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Abstract

This work examines whether the macroeconomic divide between northern and southern Italy is also present at the level of higher education. The analysis confirms that the research performance in the sciences of the professors in the south is on average less than that of the professors in the north, and that this gap does not show noticeable variations at the level of gender or academic rank. For the universities, the gap is still greater. The study analyzes some possible determinants of the gap, and provides some policy recommendations for its reduction.

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Notes

  1. This law was intended to grant increased autonomy and responsibility to the universities to establish their own organizational frameworks, including charters and regulations. Subsequently, Law 537 (Article 5) of 1993 and Decree 168 of 1996 provided further changes intended to increase university involvement in overall decision-making on use of resources, and to encourage individual institutions to operate in the market and reach their own economic and financial equilibrium.

  2. The complete list is accessible at http://attiministeriali.miur.it/UserFiles/115.htm. Last accessed on September 19, 2016.

  3. A more extensive theoretical dissertation on how to operationalize the measurement of productivity can be found in Abramo and D’Angelo (2014).

  4. Abramo et al. (2012b) demonstrated that this is the best-performing scaling factor.

  5. Because of its discrete character, the percentile scale may mislead the interpretation of productivity differences between north and south. 25 % lower average productivity in the south results in only 6.4 percentile difference.

  6. From this point, for “average productivity” we will use the average percentile rank by FSS rather than the average FSS, which would be affected by the presence of outliers.

  7. The SDSs excluded are: CHIM/05, FIS/08, GEO/12, ING-IND/18, ING-IND/20, ING-IND/30, MED/47, ING-IND/01, ING-IND/02, ING-IND/23.

References

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2011a). The dangers of performance-based research funding in non-competitive higher education systems. Scientometrics, 87(3), 641–654.

    Article  Google Scholar 

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2012a). The dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems. Journal of Informetrics, 6(2), 155–168.

    Article  Google Scholar 

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2012b). Revisiting size effects in higher education research productivity. Higher Education, 63(6), 701–717.

    Article  Google Scholar 

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2012c). Revisiting the scaling of citations for research assessment. Journal of Informetrics, 6(4), 470–479.

    Article  Google Scholar 

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2013a). Individual research performance: A proposal for comparing apples to oranges. Journal of Informetrics, 7(2), 528–539.

    Article  Google Scholar 

  • Abramo, G., Cicero, T., & D’Angelo, C. A. (2015a). Should the research performance of scientists be distinguished by gender? Journal of Informetrics, 9(1), 25–38.

    Article  Google Scholar 

  • Abramo, G., & D’Angelo, C. A. (2014). How do you define and measure research productivity? Scientometrics, 101(2), 1129–1144.

    Article  Google Scholar 

  • Abramo, G., & D’Angelo, C. A. (2015a). Accounting for gender research performance differences in ranking universities. Current Science, 109(10), 1783.

    Article  Google Scholar 

  • Abramo, G., & D’Angelo, C. A. (2015b). The VQR, Italy’s second national research assessment: Methodological failures and ranking distortions. Journal of the American Society for Information Science and Technology, 66(11), 2202–2214.

    Google Scholar 

  • Abramo, G., & D’Angelo, C. A. (2016a). A farewell to the MNCS and like size-independent indicators. Journal of Informetrics, 10(3), 646–651.

    Article  Google Scholar 

  • Abramo, G., & D’Angelo, C. A. (2016b). A farewell to the MNCS and like size-independent indicators: Rejoinder. Journal of Informetrics, 10(3), 679–683.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Di Costa, F. (2014a). Inefficiency in selecting products for submission to national research assessment exercises. Scientometrics, 98(3), 2069–2086.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Di Costa, F. (2014b). Investigating returns to scope of research fields in universities. Higher Education, 68(1), 69–85.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., Di Costa, F., & Solazzi, M. (2011b). The role of information asymmetry in the market for university-industry research collaboration. The Journal of Technology Transfer, 36(1), 84–100.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Rosati, F. (2013b). The importance of accounting for the number of co-authors and their order when assessing research performance at the individual level in the life sciences. Journal of Informetrics, 7(1), 198–208.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Rosati, F. (2013c). Measuring institutional research productivity for the life sciences: The importance of accounting for the order of authors in the byline. Scientometrics, 97(3), 779–795.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Rosati, F. (2014c). Career advancement and scientific performance in universities. Scientometrics, 98(2), 891–907.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Rosati, F. (2014d). Relatives in the same university faculty: Nepotism or merit? Scientometrics, 101(1), 737–749.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Rosati, F. (2015b). The determinants of academic career advancement: Evidence from Italy. Science and Public Policy, 42(6), 761–774.

    Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Rosati, F. (2016). A methodology to measure the effectiveness of academic recruitment and turnover. Journal of Informetrics, 10(1), 31–42.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Solazzi, M. (2010). National research assessment exercises: A measure of the distortion of performance rankings when labor input is treated as uniform. Scientometrics, 84(3), 605–619.

    Article  Google Scholar 

  • Aiello, F., & Scoppa, V. (2000). Uneven regional development in Italy: explaining differences in productivity levels. Giornale degli Economisti e Annali di Economia, 270–298.

  • Aiello, F., & Scoppa, V. (2006). Convergence and regional productivity divide in Italy: Evidence from panel data. In Proceedings of XXVII Italian regional science association conference, Pisa.

  • Allesina, S. (2011). Measuring nepotism through shared last names: The case of Italian academia. PLoS ONE, 6(8), e21160.

    Article  Google Scholar 

  • Annoni, P., & Dijkstra, L. (2013). EU Regional Competitiveness Index RCI 2013, Report EUR 26060.

  • Anselin, L., Varga, A., & Acs, Z. J. (1997). Local geographic spillovers between university research and high technology innovations. Journal of Urban Economics, 42, 422–448.

    Article  Google Scholar 

  • ANVUR. (2014). Rapporto sullo stato del sistema universitario e della ricerca 2013. Last accessed on September 19, 2016 at http://www.anvur.org/attachments/article/644/Rapporto%20ANVUR%202013_UNIVERSITA%20e%20RICERCA_integrale.pdf.

  • ANVUR. (2016). Rapporto biennale sullo stato del sistema universitario e della ricerca 2016. Last accessed on September 19, 2016 at http://www.anvur.org/attachments/article/1045/ANVUR_Rapporto_INTEGRALE_~.pdf.

  • Aprile, P. (2010). Terroni. Tutto quello che è stato fatto perché gli italiani del Sud diventassero meridionali. Milan: Edizioni Piemme.

    Google Scholar 

  • Autant-Bernard, C. (2001). Science and knowledge flows: evidence from the French case. Research Policy, 30(7), 1069–1078.

    Article  Google Scholar 

  • Baccini, A. (2016). Napoleon and the bibliometric evaluation of research: Considerations on university reform and the action of the national evaluation agency in italy. [Napoléon et l’évaluation bibliométrique de la recherche: Considérations sur la réforme de l’universitéet sur l’action de l’agence nationale d’évaluation en Italie]. Canadian Journal of Information and Library Science, 40(1), 37–57.

    Google Scholar 

  • Baccini, A., & de Nicolao, G. (2016). Do they agree? Bibliometric evaluation versus informed peer review in the Italian research assessment exercise. Scientometrics, 108(3), 1–21.

    Google Scholar 

  • Balconi, M., & Laboranti, A. (2006). University–industry interactions in applied research: The case of microelectronics. Research Policy, 35, 1616–1630.

    Article  Google Scholar 

  • Banfi, A., & Viesti, G. (2015). “Meriti” e “bisogni” nel finanziamento del sistema universitario italiano, Working papers RES 03/2015.

  • Banfield, E. C. (1958). The moral basis of a backward society. New York: Free Press.

    Google Scholar 

  • Beraldo, S. (2010). Do differences in IQ predict Italian north–south differences in income? A methodological critique to Lynn. Intelligence, 38(5), 456–461.

    Google Scholar 

  • Bonaccorsi, A., & Daraio, C. (2005). Exploring size and agglomeration effects on public research productivity. Scientometrics, 63(1), 87–120.

    Article  Google Scholar 

  • Cafagna, L. (1989). La questione delle origini del dualismo economico Italiano. In L. Cafagna (Ed.), Dualismo e sviluppo nella storia d’Italia (pp. 187–220). Marsilio: Venezia.

    Google Scholar 

  • Cannari, L., Magnani, M., & Pellegrini, G. (2010). Critica della regione meridionale. Il Sud e le politiche pubbliche. Editori Laterza: Bari.

    Google Scholar 

  • Cappelletti Montano, B. (2015). Punti organico: in 4 anni il Nord si è preso 700 ricercatori dal Centro-Sud. ROARS, 18/08/2015. Last accessed on September 19, 2016 at: http://www.roars.it/online/?p=45227.

  • Carl, N. (2014). Does intelligence explain the association between generalized trust and economic development? Intelligence, 47(6), 83–92.

    Article  Google Scholar 

  • Cornoldi, C., Belacchi, C., Giofrè, D., Martini, A., & Tressoldi, P. (2010). The mean Southern Italian children IQ is not particularly low: A reply to R. Lynn (2010). Intelligence, 38(5), 462–470.

    Article  Google Scholar 

  • D’Angelo, C. A., Giuffrida, C., & Abramo, G. (2011). A heuristic approach to author name disambiguation in large-scale bibliometric databases. Journal of the American Society for Information Science and Technology, 62(2), 257–269.

    Article  Google Scholar 

  • Daniele, V. (2015). Two Italies? Genes, intelligence and the Italian north–south economic divide. Intelligence, 49(2), 44–56.

    Article  Google Scholar 

  • Daniele, V., & Malanima, P. (2007). Il prodotto delle regioni e il divario Nord-Sud in Italia (1861–2004). Rivista di politica economica, 97(2), 267–316.

    Google Scholar 

  • Daniele, V., & Malanima, P. (2011). Il divario Nord-Sud in Italia, 1861–2011. Soveria Mannelli (Italy): Rubbettino Editore.

    Google Scholar 

  • Daniele, V., & Malanima, P. (2014). Perché il Sud è rimasto indietro? Il Mezzogiorno fra storia e pubblicistica. Rivista di storia economica, 30(1), 3–36.

    Google Scholar 

  • Durante, R., Labartino, G. & Perotti, R. (2011). Academic dynasties: Decentralization and familism in the Italian academia, NBER working paper no. 17572. Cambridge, MA: National Bureau of Economic Research.

  • Eckaus, R. S. (1960). L’esistenza di differenze economiche tra Nord e Sud d’Italia al tempo dell’unificazione. Moneta e Credito, 51, 347–372.

    Google Scholar 

  • Eckaus, R. S. (1961). The Nord–South differential in Italian economic development. The Journal of Economic History, 21(03), 285–317.

    Article  Google Scholar 

  • Eckaus, R. S. (1969). Il divario Nord-Sud nei primi decenni dell’Unità. In A. Caracciolo (Ed.), La formazione dell’Italia industriale (pp. 223–243). Laterza: Bari (Italy).

    Google Scholar 

  • Esposto, A. G. (1992). Italian industrialization and the Gerschenkronian “great spurt”: A regional analysis. The Journal of Economic History, 52(02), 353–362.

    Article  Google Scholar 

  • Esposto, A. G. (1997). Estimating regional per capita income: Italy, 1861–1914. Journal of European Economic History, 26(3), 585–604.

    Google Scholar 

  • Felice, E. (2014). Perché il Sud è rimasto indietro. Bologna: Il Mulino.

    Google Scholar 

  • Felice, E., & Giugliano, F. (2011). Myth and reality: A response to Lynn on the determinants of Italy’s north–south imbalances. Intelligence, 39(1), 1–6.

    Article  Google Scholar 

  • Fox, M. F. (1983). Pubblication productivity among scientists: A critical review. Social Studies of Science, 13(2), 285–305.

    Article  Google Scholar 

  • Francalacci, P. (2015). Punti organico: chi ha avuto e chi ha dato. ROARS, 05/10/2015. Last accessed on September 19, 2016 at http://www.roars.it/online/?p=46127.

  • Franco, G. (2013). The scientific sector MED44 facing the task of assessing the quality of research (2004–2010) of the ANVUR (national agency of assessing university research): Lights and shadows]. [Il settore scientifico-disciplinare MED44 di fronte all’esercizio di valutazione della qualità della ricerca (VQR 2004-2010) dell’ANVUR: luci e ombre. La Medicina Del Lavoro, 104(6), 483–485.

    Google Scholar 

  • Golden, J., & Carstensen, F. V. (1992). Academic research productivity, department size and organization: Further results, comment. Economics of Education Review, 11(2), 169–171.

    Article  Google Scholar 

  • ISTAT. (2015a). Conti economici territoriali. Last accessed on September 19, 2016 at http://www.istat.it/it/archivio/148152.

  • ISTAT. (2015b). Spesa per ricerca e sviluppo per regione. Last accessed on September 19, 2016 at http://noi-Italy.istat.it/fileadmin/user_upload/allegati/S14I01M02p0_2014_02.xls.

  • ISTAT. (2015c). Rapporto Bes 2015: il benessere equo e sostenibile in Italia. Last accessed on September 19, 2016 at http://www.istat.it/it/files/2015/12/Rapporto_BES_2015.pdf.

  • Jaffe, A. B. (1989). Real effects of academic research. American Economic Review, 79(5), 957–970.

    Google Scholar 

  • Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Bibliometrics: Global gender disparities in science. Nature, 504(7479), 211–213.

    Article  Google Scholar 

  • Long, J. S. (1992). Measure of sex differences in scientific productivity. Social Forces, 71(1), 159–178.

    Article  Google Scholar 

  • Lynn, R. (2010). In Italy, north–south differences in IQ predict differences in income, education, infant mortality, stature, and literacy. Intelligence, 38(1), 93–100.

    Article  Google Scholar 

  • Lynn, R. (2012). IQs in Italy are higher in the north: A reply to Felice and Giugliano. Intelligence, 40(3), 255–259.

    Article  Google Scholar 

  • Mauleón, E., & Bordons, M. (2006). Productivity, impact and publication habits by gender in the area of Materials Science. Scientometrics, 66(1), 199–218.

    Article  Google Scholar 

  • Niceforo, A. (1901). Italiani del nord e italiani del sud (Vol. 34). Torino: Fratelli Bocca.

    Google Scholar 

  • Perotti, R. (2008). L’università truccata. Einaudi, Italy. ISBN 978-8-8061-9360-7.

  • Piffer, D., & Lynn, R. (2014). New evidence for differences in fluid intelligence between north and south Italy and against school resources as an explanation for the north–south IQ differential. Intelligence, 46(5), 246–249.

    Article  Google Scholar 

  • Putnam, R., Leonardi, R., & Nanetti, R. (1993). Making democracy work: Civic traditions in modern Italy. Princeton: Princeton University Press.

    Google Scholar 

  • Sánchez-Barrioluengo, M. (2014). ‘Turning the tables’: Regions shaping university performance. Regional Studies, Regional Science, 1(1), 276–285.

    Article  Google Scholar 

  • Scoppa, V. (2007). Quality of human and physical capital and technological gaps across Italian regions. Regional Studies, 41(5), 585–599.

    Article  Google Scholar 

  • Seglen, P. O., & Asknes, D. G. (2000). Scientific productivity and group size: A bibliometric analysis of Norwegian microbiological research. Scientometrics, 49(1), 123–143.

    Article  Google Scholar 

  • SVIMEZ. (2015). Rapporto SVIMEZ 2015 sull’economia del Mezzogiorno. Last accessed on September 19, 2016 at http://www.svimez.info/index.php?option=com_content&view=article&id=348&Itemid=127&lang=it.

  • Trigilia, C. (2012). Non c’è Sud senza Nord. Perché la crescita dell’Italia si decide nel Mezzogiorno. Bologna: Il Mulino.

    Google Scholar 

  • Viesti, G. (2015). Nuovi divari. Un’indagine sulle Università del Nord e del Sud. Rapporto RES (Istituto di Ricerca Economia e Società in Sicilia). Last accessed on September 19, 2016 at http://www.resricerche.it/media/allegati/sintesi%20della%20ricerca_2015.pdf.

  • Waltman, L., Van Eck, N. J., Van Leeuwen, T. N., Visser, M. S., & Van Raan, A. F. J. (2011). Towards a new crown indicator: Some theoretical considerations. Journal of Informetrics, 5(1), 37–47.

    Article  Google Scholar 

  • Xie, Y., & Shauman, K. A. (2004). Women in science: Career processes and outcomes (review). Social Forces, 82(4), 1669–1671.

    Article  Google Scholar 

  • Zagaria, C. (2007). Processo all’università. Cronache dagli atenei Italiani tra inefficienze e malcostume. ISBN 978-8-8220-5365-7, Dedalo, Italy.

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Abramo, G., D’Angelo, C.A. & Rosati, F. The north–south divide in the Italian higher education system. Scientometrics 109, 2093–2117 (2016). https://doi.org/10.1007/s11192-016-2141-9

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