Social network analysis methods and the geography of education: regional divides and elite circuits in the school to university transition in the UK

Gamsu, Sol; Donnelly, Michael

Abstract

This paper uses social network analysis methods to explore how the spatial mobility of students to attend university creates regional divisions and socio‐spatial hierarchies of schools and universities. Using community detection methods as our methodological lens we stitch together regional economic geography, the student mobilities literature and the sociological and geographical analysis of elite education. Combining these statistical techniques with qualitative data from our broader study, we explore student flows between different geographical areas in the UK for universities. The clusters or ‘communities’ of areas underline how student migration to attend university in the UK is a moment which reflects and re‐creates regional and national boundaries. The second part of the paper examines school to university student flows, highlighting a distinctive, predominantly English cluster of elite schools and universities. Examining student mobility patterns with network methods allows us to distinguish a distinctive archipelagic geography of elite formation through higher education.

Citation

Gamsu, S., & Donnelly, M. (2021). Social network analysis methods and the geography of education: regional divides and elite circuits in the school to university transition in the UK. Journal of Economic and Human Geography, 112(4), 370-386. https://doi.org/10.1111/tesg.12413

• Journal Article Type: Article
• Acceptance Date: Mar 18, 2020
• Online Publication Date: Jun 9, 2020
• Publication Date: Aug 4, 2021
• Deposit Date: Mar 18, 2020
• Publicly Available Date: Feb 3, 2021
• Journal: Tijdschrift voor economische en sociale geografie
• Print ISSN: 0040-747X
• Electronic ISSN: 1467-9663
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 112
• Issue: 4
• Pages: 370-386
• DOI: https://doi.org/10.1111/tesg.12413
• Public URL: https://durham-repository.worktribe.com/output/1275161