Physical models and embodied cognition
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Physical models and embodied cognition Ulrich E. Stegmann1 Received: 23 March 2018 / Accepted: 31 August 2018 © The Author(s) 2018
Abstract Philosophers have recently paid more attention to the physical aspects of scientific models. The attention is motivated by the prospect that a model’s physical features strongly affect its use and that this suggests re-thinking modelling in terms of extended or distributed cognition. This paper investigates two ways in which physical features of scientific models affect their use and it asks whether modelling is an instance of extended cognition. I approach these topics with a historical case study, in which scientists kept records not only of their findings, but also of some the mental operations that generated the findings. The case study shows how scientists can employ a physical model (in this case diagrams on paper) as an external information store, which allows alternating between mental manipulations, recording the outcome externally, and then feeding the outcome back into subsequent mental manipulations. The case study also demonstrates that a models’ physical nature allows replacing explicit reasoning with visuospatial manipulations. I argue, furthermore, that physical modelling does not need to exemplify a strong kind of extended cognition, the sort for which external features are mereological parts of cognition. It can exemplify a weaker kind, instead. Keywords Task decomposition · Visuospatial reasoning · Mental rotation · Crick · Gamow · Protein synthesis Recent work on scientific models has emphasised their material nature (e.g. Giere 2002; Knuuttila 2011; Kuorikoski and Ylikoski 2015). Even abstract models are said to be physical insofar as the notation systems used to explore them involve physical marks, e.g. mathematical equations on a piece of paper (Knuuttila 2011). The emphasis on a model’s physicality is motivated by the view that the efficiency of scientific modelling hinges on the extent to which models have a physical reality, as opposed to being merely imagined. Since the use of models is an important part of understanding their role in science, it is important to understand how a model’s physicality affects its
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Ulrich E. Stegmann [email protected] School of Divinity, History and Philosophy, University of Aberdeen, 50-52 College Bounds, High Street, Aberdeen AB24 3UB, UK
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Synthese
use.1 In addition, it has been argued that the physicality of models requires re-thinking the cognitive foundations of modelling practice. Arguably, modelling is an instance of “distributed cognition” (Giere 2002; Nersessian 2006). This paper addresses two questions. First, how exactly does the physicality of models affect their use? According to one answer, physicality enables models to be employed as external information stores. On this view, models are “material objects that can be used to keep score of inferential moves and in this way be used to help in reasoning about the phenomena of interest” (Kuorikoski and Ylikoski 2015, p. 3818). Although plausible
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