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Fakultät für Biologie, Chemie und Geowissenschaften

Lehrstuhl für Ökologische Modellbildung - Prof. Dr. Michael Hauhs

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Hauhs, M; Trancón y Widemann, B; Klute, G: Bridging disciplinary gaps in studies of human-environment relations: A modelling framework, Modern Africa: Politics, History and Society, 5(2), 35-76 (2017), doi:10.26806/modafr.v5i2.196
Abstract:
Modern human-environment relations are problematic and difficult to analyse in terms of nature and culture. Many authors suggest to abandon and overcome the nature-culture dichotomy in order to reorganise the academic division of labour, not only on environmental questions. Anthropologist Philippe Descola, for example, surveyed the empirical evidence of patterns in humanenvironmental relations, suggesting four abstract cosmologies. Here, we propose a translation into a modelling terminology, which is compatible with the formalisation of programmes in computer science. The generalised framework contains four ideal types of modelling paradigms. It can be tested on various other classification schemes in a number of disciplines. In each application, the categories of classification can be translated and then the patterns of the four logic types can be compared with the phenomenology of each case. Implications for interdisciplinary cooperation between science and the humanities are sketched for some environmental issues. This work demonstrates how tools from computer science can help, metaphorically, conceptually and technically, to organise interdisciplinary exchanges between science and the humanities. The categorical approach of applying the “divide and conquer” technique to different disciplinary models serves as a yardstick for comparing the implicit logic and modelling assumptions across examples whose phenomenological contents appear as unrelated. It gives useful hints how a dilemma of choosing between rigorous or relevant models can be resolved (e.g., in environmental science) and how the nature-culture dichotomy might be replaced by a general and flexible framework of a few model types.
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