Inconsistent idealizations and inferentialism about scientific representation

Abstract

Inferentialists about scientific representation hold that an apparatus's representing a target system consists in the apparatus allowing "surrogative inferences" about the target. I argue that a serious problem for inferentialism arises from the fact that many scientific theories and models contain internal inconsistencies. Inferentialism, left unamended, implies that inconsistent scientific models have unlimited representational power, since an inconsistency permits any conclusion to be inferred. I consider a number of ways that inferentialists can respond to this challenge before suggesting my own solution. I develop an analogy to exploitable glitches in a game. Even though inconsistent representational apparatuses may in some sense allow for contradictions to be generated within them, doing so violates the intended function of the apparatus's parts and hence violates representational "gameplay."

The Value of Knowledge in the Age of Globalization Challenges: Philosophical and Intellectual Context

“…In fact, the negative elements of the development of the present are much less appreciated by researchers. For example, forecasting analysts distinguish at least three types of future development scenarios: normative, exploratory, and unpredictable (Kedar & Hon, 2020;Tan, 2021;Osiński, 2021). The exploratory scenario is open due to indicative development forecasts.…”

Idealization, representation, and explanation in the sciences

“…He suggests instead adopting "Aristotelian realism"-where mathematics refer to real mathematical properties possessed by physical systems-as one possible view by which mathematical facts can function as explainers in distinctively mathematical explanations. Tan (2021) addresses the issue of what it takes for some apparatus to count as a scientific representation of a given system. According to the inferentialist account, the representational relation between a model and its target is constituted by the model's inferential capacity; or, put otherwise, it is the fact that cognitive agents can make use of a model by drawing surrogative inferences is what constitutes the model's representational status.…”

“…A second theme emerging from the papers in this special issue is the impact that various conceptualizations of idealization have on our abilities to offer scientific explanations, to produce an analysis of what explanations are or should be, and to understand scientific representation. Peter Tan (2021) suggests amending inferentialist accounts of scientific representation to account for inconsistent idealizations. Michael Strevens (2021) advocates a view wherein the introduction of idealizations into a model is legitimate so long as it pertains to non-difference-making factors, arguing for a logical reading of the notion of difference-making.…”