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Evaluating social science and humanities knowledge production: an exploratory analysis of dynamics in science systems
Authors:Patricia van Hemert  Peter Nijkamp  Jolanda Verbraak
Institution:1. VU Center for Entrepreneurship , VU University Amsterdam , De Boelelaan 1085, 1081, Amsterdam, HV, the Netherlands;2. Department of Spatial Economics , VU University Amsterdam , De Boelelaan 1105, 1081, Amsterdam, HV, the Netherlands
Abstract:Knowledge is gaining increasing importance in modern-day society as a factor of production and, ultimately, growth. This article explores the dynamics in university knowledge production and its effect on the state of university–industry–policy exchange in the Netherlands. Science systems are said to be in transformation. The university has evolved from performing conventional research and educational functions to serving as an innovation-promoting knowledge hub; dynamics that have received mixed reactions. The social sciences and humanities (SSH) take a special position, insofar as their focus seems primarily to be placed on conventional research and educational functions, and not directly on (commercial) valorization. Societal changes are, however, pressing for a reconsideration of the role of SSH. In our article, we distinguish between three important new movements that seem to be affecting SSH. It is believed that these movements, which are already having an impact today, will considerably influence SSH in the future. These developments are further differentiation, synthesis between the various subdisciplines of SSH and the natural sciences, and shifts in paradigms. The aims of this article are twofold: (1) to assess what is believed to be the most likely development of SSH by means of discovering relevant subsets of factors influencing university knowledge production; and (2) to discover whether the knowledge production factors show characteristics of a general development similar to the “Mode 2” concept. A systematic qualitative database was created by means of 22 semi-structured personal interviews with key representatives from business, university and the policy sector. Our explanatory framework employs an artificial intelligence method, i.e. rough set analysis. On the basis of these results, we find that a small minority of the respondents prefers a closer relationship of SSH to society, government and industry, and other institutional centers of authority, whilst interdisciplinarity in particular is regarded as having an overall positive influence on the future of SSH in the Netherlands. Consequently, the idea of a clear distinction between Mode 1 and Mode 2 knowledge production, i.e. traditional knowledge and knowledge carried out in the context of application, is not supported by our data.
Keywords:science systems  knowledge production  Mode 2  SSH  rough set analysis  artificial intelligence
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