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Higher education and its contribution to a diverse regional supply of human capital: does the binary/unitary divide matters?

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Abstract

Diversity has been an important topic of research for some time in higher education, though the purposes underlying this attention have varied across national and regional contexts. In many parts of the world, the term diversity has been emphasized with regard to variety among the programs or services provided by academic institutions, and differences among the types of institutions themselves. It is particularly important to discuss whether different dimensions of diversity may influence the degree of effectiveness of higher education (HE) in fulfilling its contribution and relevance to economic and social development. We are particularly interested in analyzing whether unitary or binary systems present significant differences in different dimensions of diversity that may be relevant to enhance higher education institutions’ (HEIs) contribution to territorial cohesion, notably by enhancing the local stock of human capital and contributing to the social and cultural development of their regions. Therefore, we propose the following research questions: *Are there relevant patterns regarding different dimensions of diversity between unitary and binary HE systems? *In the case of binary systems, is it possible to find relevant differences in different dimensions of diversity between universities and more vocational HEIs? By looking at these questions, we aim at contributing both to the literature on HE institutional diversity and to the study of the role played by HEIs on regional development.

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Notes

  1. Nomenclature of territorial units for statistics (NUTS) constitutes a hierarchical system created in order to divide the economic territory of the EU. This division is carried out for harmonization purposes, namely, regarding the production of European regional statisticsand what concerns the analysis and design of European regional socio-economic policies. Within this framework, NUTS 1 constitutes the largest economic regions (being sometimes coincident with the countries themselves), while NUTS 2 corresponds, generally, to the division of NUTS 1 into smaller territorial units (regions) that are used for the application of regional policies. Finally, NUTS 3 constitutes even smaller territorial units (regions) used for specific diagnoses.

  2. Number of students concerns the number of individuals enrolled in each HEI at the beginning of the academic year (i.e., the last day of the first month of the winter semester academic year). Moreover, the total number of students is simply based on the count of students according to the previously mentioned criterion.

  3. In general, the data set excludes very small HEIs with less than 200 students and less than 30 staff members.

  4. In a nutshell, we include in our analysis data concerning all countries available in the dataset except those for which very limited information is available.

  5. http://ec.europa.eu/eurostat/statistics-explained/index.php/Urban-rural_typology_update

  6. According to this typology, study programs are categorized as “General” (00), “Education” (01), “Humanities and Arts” (02), “Social Sciences” (03), “Business and Law” (04), “Natural Sciences, Mathematics and Statistics” (05), “Information and Communication Technologies” (06), “Engineering, Manufacturing and Construction (07), “Agriculture, Forestry, Fisheries and Veterinary (08), “Health and Welfare (09), and “Services” (10).

  7. ISCED 8 courses (doctoral degrees) were not included due to the low number of enrolled students at this ISCED level. Given that Universities of Applied Sciences are not usually allowed to provide ISCED 8 programs, the analysis underestimates slightly the degree diversification level of universities when compared to UAS.

  8. Due to the number of observations (countries) in our sample, statistical inference methods were not adequate to be used to analyze the existing differences between the subsectors.

  9. In the case of HEIs that have multiple campuses in different NUTS 3, all enrolled students were counted as if they were enrolled in the headquarters of the HEI, which tends to underestimate the results obtained for the spatial diversification indexes.

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Santoalha, A., Biscaia, R. & Teixeira, P. Higher education and its contribution to a diverse regional supply of human capital: does the binary/unitary divide matters?. High Educ 75, 209–230 (2018). https://doi.org/10.1007/s10734-017-0132-2

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