Gender Studies in Entrepreneurial Universities: The Case of Inter- and Transdisciplinarity

Abstract

Gender Studies today find themselves in a paradoxical situation. They developed ‘bottom-up’ out of a social movement – that is the feminist movement – yet in many ways they turned into a ‘top-down’ project featured by university presidents and science foundations alike. This can best be illustrated with the concepts ‘inter’- and ‘transdisciplinarity’. For more than a decade, these concepts have operated as buzzwords in the abundant debates about the changing nature of knowledge, science, society, and their mutual relations. At least rhetorically they play an integral part in the restructuring of the modern western university as they serve as criteria of excellence in research assessment and teaching evaluation and as a rhetorical resource in the global competition of universities for prestige and funding as well as students and faculty. Interdisciplinarity, sociologists of knowledge Peter Weingart and Nico Stehr (2000) observe, has indeed “become a label almost synonymous with creativity and progress, signaling reform and modernization in science and scientific institutions” (Weingart/Stehr 2000: 1). Disciplinarity and academic disciplines, in contrast, are often portrait as static, rigid, immobile, backward, and resistant against (necessary) reforms. Universities, the advocates of transdisciplinarity thus argue, will only be suitable actors in future knowledge production if they overcome their discipline-based structural conservatism and recognize the emergence of a new type of knowledge that is transdisciplinary knowledge. This, scholars like Basarab Nicolescu (1997) suggest, would imply a multi-dimensional opening of the university: towards the civil society, towards other places of knowledge production, towards the cyberspace- time, towards the aim of universality, and towards a redefinition of values governing its own existence. 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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