Modeling

Michela Massimi (University of Edinburgh)
I analyse the exploratory function of two main modelling practices: targetless fictional models and hypothetical perspectival models. In both cases, I argue, modelers invite us to imagine or conceive something about the target system, which is either known to be non-existent (fictional models) or just hypothetical (in perspectival models). I clarify the kind of imagining or conceiving involved in each modelling practice, and I show how each — in its own right — delivers important modal knowledge. I illustrate these two kinds of exploratory models with Maxwell's ether model and SUSY models at the LHC.

Karim Bschir (Swiss Federal Institute of Technology ETH), Lydia Braunack-Mayer (Swiss Federal Institute of Technology ETH)
In this paper, we challenge a claim made by Frigg et al. (2014) that uncertainty about the true structure of a nonlinear model debilitates our ability to make decision-relevant predictions. We argue that Frigg et al. underrate the numerous tools of modern statistics for the handling of model uncertainty, and thus overstate the epistemic consequences of SME in general. We do concede, however, that their arguments point at serious limitations in the context of climate science. These limitations arise due to specific properties of climate models and the ensembles used in climate science.

Justin Price (University of South Carolina)
Kendall Waltons' pretense theory of fiction has recently seen application to analysis of scientific models by Roman Frigg and Adam Toon. However, Walton's pretense theory provides a problematic interpretation of assertions referring to fictional characters and places. This feature transfers to Frigg and Toon's analysis of models, leading to a problematic interpretation of what Fiora Salis calls model-world comparison, and what I call model-model comparisons. This problematic interpretation confounds Frigg and Toon's ability to account for learning through models. My contribution is to point out that these same features of the pretense account make it inadequate for depicting model transfer. I provide an example of model transfer in chemistry to motivate this point. Amie Thomasson's artifactualist account of fiction avoids the problematic interpretations while retaining the virtues of a pretense theory. We should take an artifactualist approach in analysing models as fictions.

Lena Zuchowski (University of Bristol)
Geomorphology faces unique epistemological challenges. The most prominent of these is the scale problem, i.e. the fact that geomorphological phenomena encompass process on many different spatial-temporal scales. I identify and compare two predominant methodological approaches to the scale problem: a framework approach, which aims at the provision of general frameworks for the integration of evidence, and an individualistic approach, which rejects the application of general frameworks and advocates approaching each investigation without preconditions. Furthermore, I discuss why, in this debate, philosophy of science has not been viewed as helpful by geomorphologists and what tools philosophers can bring to it.

Lachlan Walmsley (Australian National University)
Models are essential scientific tools that scientists use to make inferences and build theories and that policy-makers use to inform their decisions. But models are imperfect representations of their real-world targets, containing simplifications and distortions called idealizations. According to Michael Weisberg there are three kinds of idealization: Galilean idealization, minimalist idealization, and multi-model idealization (MMI). In this paper, I argue that Weisberg's notion of minimalist idealization is too minimal and that his notion of MMI mischaracterizes an important instance of multi-modelling in science today, that is, ensemble modelling in climate science, and should not be considered a kind of idealization at all.