From Models-as-Fictions to Models-as-Tools

Abstract

Many accounts of scientific modeling conceive of models as fictions: there are analogies between models and various aesthetic objects, as well as between how scientists interact with models and how authors interact with fictions. Fictionalists, like most accounts of models, take models to be revelatory of the actual world in virtue of bearing some resemblance relation to a target system. While such fictionalist accounts capture crucial aspects of modelling practice, they are ill-suited to some design and engineering contexts. Here, models sometimes serve to underwrite design projects whereby real-world targets are constructed. in such circumstances, it is unclear what the model is supposed to resemble. Further, while fictionalists often require that models qua models have their content in virtue of construal or interpretation, in some engineering and design contexts success-conditions do not require such content-all that is required is that the model generates the required outputs. i take these points to motivate a view which accommodates fictionalism, but is broader. i articulate and defend an account of models as tools: specifically, material objects which are put to particular uses in particular contexts.

Epistemic Engagement, Aesthetic Value, and Scientific Practice

“…One needn't adopt as all-pervasive a view on idealizations as Potochnik, nor fictionalism about scientific models (indeed, I don't: Currie [2017]), to see the problem. If aesthetic judgements are as widespread in scientific practice as Turner argues, especially if aesthetic judgements play a role in shaping and guiding scientists, and the aesthetic is made more rich via truth, then scientists spending so much time intimately engaged with tools and techniques which they explicitly do not believe to be true is mysterious.…”

Philosophical Perspectives on Earth System Modeling: Truth, Adequacy, and Understanding

“…An alternative perspective sees models as tools that scientists wish to use for particular predictive, explanatory, and other purposes (Currie, ; Giere, ; Knuuttila, ; Morrison & Morgan, ). Model evaluation is conceptualized as an activity that seeks to learn whether a model is adequate for one or more purposes of interest (for related views, see Caswell, ; Rykiel, ; NRC, ; Parker, ; Baumberger et al, ).…”

“…(see, e.g., Teller, 2001, discussing the "Perfect Model Model" and Knuuttila, 2011, p.267, on "the idea that scientific representation should aim for as accurate a representation as possible.") An alternative perspective sees models as tools that scientists wish to use for particular predictive, explanatory, and other purposes (Currie, 2018;Giere, 2004;Knuuttila, 2011;Morrison & Morgan, 1999). Model evaluation is conceptualized as an activity that seeks to learn whether a model is adequate for one or more purposes of interest (for related views, see Caswell, 1976;Rykiel, 1996;NRC, 2007;Parker, 2009;Baumberger et al, 2017).…”

Data models, representation and adequacy-for-purpose

“…In conjunction with the rise of this representational perspective, there has also been a pragmatic turn: many philosophers now emphasize that scientific modeling is an activity undertaken by agents with specific goals and purposes in mind, such as the prediction or explanation of a particular phenomenon. That is, models are not just representations; they are also tools, which are constructed or selected, and manipulated, with an eye toward achieving specific epistemic or practical purposes (e.g., Morrison and Morgan 1999 ; Giere 2004 , 2010 ; Boon and Knuuttila 2009 ; Parker 2010 ; Knuuttila 2011 ; Currie 2018 ; Boon 2020 ). A closely-related view of model evaluation proposes that models be judged in terms of their adequacy or fitness for particular purposes, rather than by comparison to some abstract standard of perfect representation (Parker 2010 , 2020a ; Currie 2018 ; see also Teller 2001 ; NRC 2007 ; Taper et al 2008 ).…”