Scientific output scales with resources. A comparison of US and European universities
Autoři:
Benedetto Lepori aff001; Aldo Geuna aff002; Antonietta Mira aff004
Působiště autorů:
Faculty of Communication Sciences, Università della Svizzera Italiana, Lugano, Switzerland
aff001; Department of Economics and Statistics Cognetti De Martiis, University of Turin, Turin, Italy
aff002; BRICK, Collegio Carlo Alberto, Turin, Italy
aff003; Institute of Computational Sciences, Faculty of Economics, Università della Svizzera Italiana, Lugano, Switzerland
aff004
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0223415
Souhrn
By using a comprehensive dataset of US and European universities, we demonstrate super-linear scaling between university revenues and their volume of publications and (field-normalized) citations. We show that this relationship holds both in the US and in Europe. In terms of resources, our data show that three characteristics differentiate the US system: (1) a significantly higher level of resources for the entire system, (2) a clearer distinction between education-oriented institutions and doctoral universities and (3) a higher concentration of resources among doctoral universities. Accordingly, a group of US universities receive a much larger amount of resources and have a far higher number of publications and citations when compared to their European counterparts. These results demonstrate empirically that international rankings are by and large richness measures and, therefore, can be interpreted only by introducing a measure of resources. Implications for public policies and institutional evaluation are finally discussed.
Klíčová slova:
Social sciences – Europe – Citation analysis – Public policy – Bibliometrics – United States – Government funding of science – Institutional funding of science
Zdroje
1. Geuna A. The changing rationale for European university research funding. Journal of economic issues. 2001;35: 607–632.
2. Stephan P. The Endless Frontier: Reaping What Bush Sowed? In: Jaffe AB, Jones BF, editors. The changing frontier. Rethinking Science and Innovation Policy. Chicago: Chicago University Press; 2013. pp. 321–370.
3. Hicks D. Performance-based university research funding systems. Research policy. 2012;41: 251–261.
4. Dasgupta P, David PA. Toward a new economics of science. Research policy. 1994;23: 487–521.
5. Slaughter S, Leslie L. Academic Capitalism: Politics, Policies, and the Entrepreneurial University. Baltimore: Johns Hopkins University Press; 1997.
6. Leydesdorff L, Wouters P, Bornmann L. Professional and citizen bibliometrics: complementarities and ambivalences in the development and use of indicators—a state-of-the-art report. Scientometrics. 2016;109: 2129–2150. doi: 10.1007/s11192-016-2150-8 27942086
7. Van Raan AF. Fatal attraction: Conceptual and methodological problems in the ranking of universities by bibliometric methods. Scientometrics. 2005;62: 133–143.
8. Marginson S, Van der Wende M. To rank or to be ranked: The impact of global rankings in higher education. Journal of studies in international education. 2007;11: 306–329.
9. Shin JC, Toutkoushian RK, Teichler U. University rankings: Theoretical basis, methodology and impacts on global higher education: Springer Science & Business Media; 2011.
10. Taylor BJ, Cantwell B. Global competition, US research universities, and international doctoral education: Growth and consolidation of an organizational field. Research in Higher Education. 2015;56: 411–441.
11. Hazelkorn E. Rankings and the battle for world-class excellence: institutional strategies and policy choices. Higher Education Management and Policy. 2009;21/1.
12. Bonaccorsi A, Cicero T, Haddawy P, Hassan S. Explaining the transatlantic gap in research excellence. Scientometrics. 2017;110: 217–241.
13. Paradeise C, Thoenig J. Academic Institutions in Search of Quality: Local Orders and Global Standards. Organ Stud. 2013;34: 189–218.
14. Merton RK. The Matthew Effect in Science. The reward and communication systems of science are considered. Science. 1968;159(3810): 56–63.
15. Hicks D, Wouters P, Waltman L, De Rijcke S, Rafols I. Bibliometrics: the Leiden Manifesto for research metrics. Nature. 2015;520: 429–431. doi: 10.1038/520429a 25903611
16. Vernon MM, Balas EA, Momani S. Are university rankings useful to improve research? A systematic review. PloS one. 2018;13: e0193762. doi: 10.1371/journal.pone.0193762 29513762
17. Katz JS. The self-similar science system. Research policy. 1999;28: 501–517.
18. Nomaler Ö, Frenken K, Heimeriks G. On scaling of scientific knowledge production in US metropolitan areas. PloS one. 2014;9: e110805. doi: 10.1371/journal.pone.0110805 25353686
19. van Raan AF. Universities scale like cities. PloS one. 2013;8: e59384. doi: 10.1371/journal.pone.0059384 23544062
20. Waltman L, van Eck NJ. Field-normalized citation impact indicators and the choice of an appropriate counting method. Journal of Informetrics. 2015;9: 872–894.
21. Abramo G, D’Angelo CA. A farewell to the MNCS and like size-independent indicators. Journal of Informetrics. 2016;10: 646–651.
22. Brinkman PT, Leslie LL. Economies of Scale in Higher Education: Sixty Years of Research. Review of Higher Education. 1986;10: 1–28.
23. Daraio C, Bonaccorsi A, Simar L. Efficiency and economies of scale and specialization in European universities: A directional distance approach. Journal of Informetrics. 2015;9: 430–448.
24. [Anonymous]. DORA—San Francisco Declaration. https://sfdora.org.
25. National Center for Educational Statistics. Integrated Postsecondary Educational Data System (IPEDS). http://nces.ed.gov/ipeds/.
26. European Commission. European Tertiary Education Register (ETER). http://www.eter-project.com.
27. The Carnegie Foundation. Carnegie Classification of US universities. http://carnegieclassifications.iu.edu.
28. Waltman L, Calero‐Medina C, Kosten J, Noyons E, Tijssen RJ, Eck NJ, et al. The Leiden Ranking 2011/2012: Data collection, indicators, and interpretation. J Am Soc Inf Sci Technol. 2012;63: 2419–2432.
29. Waltman L, Calero‐Medina C, Kosten J, Noyons EC, Tijssen RJ, van Eck NJ, et al. The Leiden Ranking 2011/2012: Data collection, indicators, and interpretation. J Am Soc Inf Sci Technol. 2012;63: 2419–2432.
30. Leitao JC, Miotto JM, Gerlach M, Altmann EG. Is this scaling nonlinear? arXiv preprint arXiv:1604.02872. 2016.
31. Hansen CB. Generalized least squares inference in panel and multilevel models with serial correlation and fixed effects. J Econ. 2007;140: 670–694.
32. Koenker R, Hallock KF. Quantile regression. Journal of economic perspectives. 2001;15: 143–156.
33. MacKinnon D. Introduction to statistical mediation analysis. New York: Taylor & Francis; 2007.
34. Archambault É, Campbell D, Gingras Y, Larivière V. Comparing bibliometric statistics obtained from the Web of Science and Scopus. J Am Soc Inf Sci Technol. 2009;60: 1320–1326.
35. Bettencourt LM. The origins of scaling in cities. Science. 2013;340: 1438–1441. doi: 10.1126/science.1235823 23788793
36. Geiger RL. Research and relevant knowledge: American research universities since World War II. Oxford: Oxford University Press; 1993.
37. Cohen AM. The shaping of American higher education: Emergence and growth of the contemporary system: John Wiley & Sons; 2007.
38. Daraio C, Bonaccorsi A, Geuna A, Lepori B, Bach L, Bogetoft P, et al. The European university landscape. Research policy. 2011;40: 148–164. doi: 10.1016/j.respol.2010.10.009
39. Weerts DJ, Ronca JM. Understanding differences in state support for higher education across states, sectors, and institutions: A longitudinal study. The Journal of Higher Education. 2012;83: 155–185.
40. Peterson GJ, Presse S, Dill KA. Nonuniversal power law scaling in the probability distribution of scientific citations. Proc Natl Acad Sci U S A. 2010;107: 16023–16027. doi: 10.1073/pnas.1010757107 20805513
41. Hicks D. Performance-based university research funding systems. Research Policy. 2012;41: 251–261.
42. Slaughter S, Rhoades G. Academic capitalism and the new economy: Markets, state, and higher education: JHU Press; 2004.
43. Sauder M, Espeland WN. The discipline of rankings: tight coupling and organizational change. American Sociological Review. 2009;74: 63–82.
44. Deem R, Mok KH, Lucas L. Transforming higher education in whose image? Exploring the concept of the ‘world-class’ university in Europe and Asia. Higher education policy. 2008;21: 83–97.
45. Glänzel W, Thijs B, Debackere K. Productivity, performance, efficiency, impact-What do we measure anyway?. Some comments on the paper" A farewell to the MNCS and like size-independent indicators" by Abramo and D'Angelo. Journal of Informetrics. 2016.
46. Bonaccorsi A. Explaining poor performance of European science: institutions versus policies. Science and Public Policy. 2007;34: 303–316.
47. Labaree DF. Public schools for private gain: The declining American commitment to serving the public good. Phi Delta Kappan. 2018;100: 8–13.
48. Hazelkorn E, Gibson A. 18 The impact and influence of rankings on the quality, performance and accountability agenda. Research Handbook on Quality, Performance and Accountability in Higher Education. 2018: 232.
49. Gumport Patricia J. Academic Restructuring: Organizational Change and Institutional Imperatives. Higher Education. 2000;39: 67–91. 1003859026301.
50. Lange KL, Little RJ, Taylor JM. Robust statistical modeling using the t distribution. Journal of the American Statistical Association. 1989;84: 881–896.
51. Bartolucci F, Scaccia L. The use of mixtures for dealing with non-normal regression errors. Comput Stat Data Anal. 2005;48: 821–834.
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