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Cultural Diversity and the School-To-Work Transition: A Relational Perspective

  • William G. FeigheryEmail author
Chapter
Part of the Technical and Vocational Education and Training: Issues, Concerns and Prospects book series (TVET, volume 17)

Abstract

Drawing on evidence from the European tourism sector and adopting a Bourdieusian approach, this chapter embraces a relational perspective on the school-to-work transition. Taking account of macro public policy, as well as meso organisational and micro individual social spheres, the reported study sought to develop insights on the perceived value of, and demand for, diversity in the European tourism sector. Based on data from three research instruments, it is suggested that in the European tourism sector, the school-to-work transition is in a process of transformation as a number of forces, including neo-liberalism, globalisation and the “democratisation” of education, mitigate against the normative school-to-work transition in developed economies. While deregulation and liberalisation policies have generated substantial numbers of jobs in the sector, they tend to be low-level deskilled roles undertaken by a growing number of mobile and flexible workers entering the European labour market. Also, these structural changes seem to offer fewer opportunities for a stable transition from school- to career-oriented work. This macro context provides the terrain on which cultural diversity has come to be assigned value in the discourse and praxis of social groups and organisations. Yet, despite the “value-in-diversity” rhetoric emerging from the public and private sector, evidence from this study suggests that for both tourism organisations and individuals working in, or entering, the sector, cultural diversity is represented not as a source of value-laden possibilities but as part of the structured dispositions of individual and organisational habitus.

Keywords

Labour Market European Union Social Capital Cultural Diversity Cultural Capital 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  1. 1.NeuchatelSwitzerland

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