A possible situation semantics for Scientific models and theories

Series: Logic and Philosophy

Speaker : Quentin Ruyant (UCLouvain)

Résumé : 
It has become commonplace to understand scientific theories as families of structures, its models, and to use a possible worlds semantics to analyse their content: a model is a « possible world if the theory is true ».
Philosophers of science interested in scientific practice have pointed out a number of ways in which this idealistic picture is too simplistic: scientific models are about specific systems instead of « worlds », they often distort theoretical laws, incorporate domain specific postulates or idealisations that are function of the aims of the modellers, they are not extensional but have an internal modal structure and they are constructed and applied by relying on informal « know-how » (Cartwright 1983, Morgan and Morrison 1999, Giere 2010). A standard possible world analysis isn’t fit to account for all these contextual features. However, no real alternative has been proposed so far. My aim is to programmatically sketch such an alternative: a possible situation semantics. Situations are coarse-grained, local states of affairs. A context of application can be modelled, taking inspiration from the notion of aboutness (subject matter) in philosophy of language (Yablo 2014, Fine 2017, Hawke 2018), as a partition of possibility space for a given situation, and the content of a theoretical model can then be analysed as a function from context to probabilistic weighting of the context. Contexts entertain parthood (coarse-graining) relations. In contrast with subject matters in philosophy of language, where they are purely representational choices, I will give reasons to « reify » contexts: some are associated with the interventionist nature of experimentation and others with the interpretation of quantum mechanics. The latter reason in particular motivates a research program, which consists in analysing the formal relations between contexts, and associate these relations with experimental and theoretical inferences. I will illustrate this idea with a simple measurement situation.

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