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Actor networks and the construction of applicable knowledge: the case of the Timbre Brownfield Prioritization Tool
Authors:Filip Alexandrescu  Petr Klusá?ek  Stephan Bartke  Robert Osman  Bohumil Frantál  Stanislav Martinát  Josef Kunc  Lisa Pizzol  Alex Zabeo  Elisa Giubilato  Andrea Critto  Alena Bleicher
Affiliation:1.Research Institute for the Quality of Life,Romanian Academy,Bucharest,Romania;2.Department of Environmental Sciences, Informatics and Statistics,University Ca’ Foscari of Venice,Venice,Italy;3.Institute of Geonics,Academy of Sciences of the Czech Republic,Brno,Czech Republic;4.Department of Economics,Helmholtz Centre for Environmental Research,Leipzig,Germany;5.German Environment Agency,Dessau-Ro?lau,Germany;6.School of Geographical Sciences and Urban Planning,Arizona State University,Tempe,USA;7.Department of Urban and Environmental Sociology,Helmholtz Centre for Environmental Research,Leipzig,Germany
Abstract:This article deals with experiences acquired during the process of developing the Timbre Brownfield Prioritization Tool (TBPT). Developing a decision support tool that takes into account the expectations and experiences of its potential users is similar to creating applicable knowledge by the joint action of scientists and heterogeneous actors. Actor network theory is used to explore the construction of this form of applicable knowledge as a process of actor network creation. Following the French sociologist Callon, networks are seen to be initiated and carried out by a group of scientists (tool developers) via four moments of translation, called problematization, interessement, enrolment and mobilization. Each step in the construction of the TBPT—from the initial research question to the final model—can be linked in retrospect to changing configurations of actor networks. Based on the experiences of the tool developers in the Czech Republic, Poland, Germany and Romania, we illustrate how these configurations varied across space and time. This contribution emphasizes the ability to correlate gains in knowledge with the more visible changes in the scope of actor networks in order to highlight achievements but also limitations in acquiring applicable knowledge.
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