Peter Tan

Model transfer is the scientific practice of taking a model which was initially applied in one particular kind of target system in some particular scientific domain and applying it to represent a novel target system in a novel scientific domain. This paper motivates a realist interpretation of empirically successful model transfers and the implications of such an interpretation for the metaphysics of science. The paper uses two examples of empirically successful model transfer, the first of which is a strikingly successful recent application of the Ising model to neurobiology, the second of which is Maxwell’s “method of physical analogy”. The paper first defends the need for a realist picture regarding the transfer of model templates and the apparent discovery of physical analogies. Then, it examines further the implications of such a picture, finding it to be quite revisionary in its conception of the nature of causal processes.

According to the growing block ontology of time, there (tenselessly and unrestrictedly) exist past and present objects and events, but no future objects or events. The growing block is made attractive not just because of the attractiveness of its ontological basis for past-tensed truths, the past’s fixity, and future’s openness, but by underlying principles about the right way to fill in this sort of ontology. I shall argue that given these underlying views about the connection between truth and ontology, growing blockers incur an ontological commitment to an infinite number of temporal dimensions (“hypertime”). This commitment to hypertime generates a vicious explanatory regress. It also undermines the idea that the reality of the past is sufficient to explain why truths about the past are fixed. Both of these implications are highly unattractive; growing blockers would do well to clarify what other motivations they can offer for their view and how they can avoid these consequences.

Sometimes, scientific models are either intended to or plausibly interpreted as representing nonactual but possible targets. Call this “hypothetical modeling”. This paper raises two epistemological challenges concerning hypothetical modeling. To begin with, I observe that given common philosophical assumptions about the scope of objective possibility, hypothetical models are fallible with respect to what is objectively possible. There is thus a need to distinguish between accurate and inaccurate hypothetical modeling. The first epistemological challenge is that no account of the epistemology of hypothetical models seems to cohere with the most characteristic function of scientific modeling in general, i.e., surrogative representation. The second epistemological challenge is a version of “reliability challenges” familiar from other areas. There is a challenge to explain how hypothetical models could be a reliable guide to what is possible, given that they are not and cannot be compared against their nonactual targets and updated accordingly. I close with some brief remarks on possible solutions to these challenges.

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.”

We call attention to certain cases of epistemic akrasia, arguing that they support belief-credence dualism. Belief-credence dualism is the view that belief and credence are irreducible, equally fundamental attitudes. Consider the case of an agent who believes p, has low credence in p, and thus believes that they shouldn’t believe p. We argue that dualists, as opposed to belief-firsters (who say credence reduces to belief) and credence-firsters (who say belief reduces to credence) can best explain features of akratic cases, including the observation that akratic beliefs seem to be held despite possessing a defeater for those beliefs, and that, in akratic cases, one can simultaneously believe and have low confidence in the very same proposition.

The longstanding philosophical orthodoxy on counterfactuals holds, in part, that counterfactuals with metaphysically impossible antecedents are indiscriminately vacuously true. Drawing on a number of examples from across scientific practice, I argue that science routinely treats counterpossibles as non-vacuously true and also routinely treats other counterpossibles as false. In fact, the success of many central scientific endeavors requires that counterpossibles can be non-vacuously true or false. So the philosophical orthodoxy that counterpossibles are indiscriminately vacuously true is inconsistent with scientific practice. I argue that this provides a conclusive reason to reject the orthodoxy.