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From situated knowledges to situated modelling: a relational framework for simulation modelling

Urheber*innen

Klein,  Anja
External Organizations;

Unverzagt,  Krystin
External Organizations;

Alba,  Rossella
External Organizations;

/persons/resource/Donges

Donges,  Jonathan Friedemann
Potsdam Institute for Climate Impact Research;

Hertz,  Tilman
External Organizations;

Krueger,  Tobias
External Organizations;

Lindkvist,  Emilie
External Organizations;

Martin,  Romina
External Organizations;

Niewöhner,  Jörg
External Organizations;

Prawitz,  Hannah
Potsdam Institute for Climate Impact Research;

Schlüter,  Maja
External Organizations;

/persons/resource/luana.schwarz

Schwarz,  Luana
Potsdam Institute for Climate Impact Research;

Wijermans,  Nanda
External Organizations;

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30166oa.pdf
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Zitation

Klein, A., Unverzagt, K., Alba, R., Donges, J. F., Hertz, T., Krueger, T., Lindkvist, E., Martin, R., Niewöhner, J., Prawitz, H., Schlüter, M., Schwarz, L., Wijermans, N. (2024): From situated knowledges to situated modelling: a relational framework for simulation modelling. - Ecosystems and People, 20, 1, 2361706.
https://doi.org/10.1080/26395916.2024.2361706


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_30166
Zusammenfassung
In this paper we extend the use of a relational approach to simulation modelling, a widely used knowledge practice in sustainability science. Among modellers, there is awareness that model results can only be interpreted in view of the assumptions that inform model construction and analysis, but less systematic questioning of those assumptions. Moreover, current methodological discussions tend to focus on integrating social and ecological dynamics or diverse knowledges and data within a model. Yet choices regarding types of modelling, model structure, data handling, interpretation of results and model validation are not purely epistemic. They are entangled with values, contexts of production and use, power relations, and pragmatic considerations. Situated Modelling extends a relational understanding of the world to scientific knowledge production and with that to modelling itself in order to enable a systematic interrogation of these choices and to research social-ecological transformations relationally. To make tangible the situatedness of simulation modelling, we build on existing practices and describe the situatedness of three distinct modelling approaches. We then suggest four guiding principles for Situated Modelling: 1. attending to the apparatus of knowledge production that is socially and materially embedded and produced by e.g. research infrastructures, power relations, and ways of thinking; 2. considering how agency is distributed between model, world, data, modeller in model construction; 3. creating heterogenous collectives which together occupy the formerly individualised subject position; and 4. using agonism as an epistemic virtue to retain and work with significant differentiations of social-ecological dynamics throughout the modelling process.