This monograph examines truth in fiction by applying the techniques of a naturalized logic of human cognitive practices. The author structures his project around two focal questions. What would it take to write a book about truth in literary discourse with reasonable promise of getting it right? What would it take to write a book about truth in fiction as true to the facts of lived literary experience as objectivity allows? It is argued that the most semantically distinctive feature of (...) the sentences of fiction is that they are unambiguously true and false together. It is true that Sherlock Holmes lived at 221B Baker Street and also concurrently false that he did. A second distinctive feature of fiction is that the reader at large knows of this inconsistency and isn't in the least cognitively molested by it. Why, it is asked, would this be so? What would explain it? Two answers are developed. According to the no-contradiction thesis, the semantically tangled sentences of fiction are indeed logically inconsistent but not logically contradictory. According to the no-bother thesis, if the inconsistencies of fiction were contradictory, a properly contrived logic for the rational management of inconsistency would explain why readers at large are not thrown off cognitive stride by their embrace of those contradictions. As developed here, the account of fiction suggests the presence of an underlying three - or four-valued dialethic logic. The author shows this to be a mistaken impression. There are only two truth-values in his logic of fiction. The naturalized logic of Truth in Fiction jettisons some of the standard assumptions and analytical tools of contemporary philosophy, chiefly because the neurotypical linguistic and cognitive behaviour of humanity at large is at variance with them. Using the resources of a causal response epistemology in tandem with the naturalized logic, the theory produced here is data-driven, empirically sensitive, and open to a circumspect collaboration with the empirical sciences of language and cognition. (shrink)

Though it is held that some models in science have explanatory value, there is no conclusive agreement on what provides them with this value. One common view is that models have explanatory value vis-à-vis some target systems because they are developed using an abstraction process. Though I think this is correct, I believe it is not the whole picture. In this paper, I argue that, in addition to the well-known process of abstraction understood as an omission of features or information, (...) there is also a family of abstraction processes that involve aggregation of features or information and that these processes play an important role in endowing the models they are used to build with explanatory value. After offering a taxonomy of abstraction processes involving aggregation, I show by considering in detail several models drawn from different sciences that the abstraction processes involving aggregation that are used to build these models are responsible for their having explanatory value. (shrink)

The most discussed puzzle about weakness of will (WoW) is how it is possible: how can a person freely and intentionally perform actions that she judges she ought not perform, or that she has resolved not to perform? In this paper, we are concerned with a much less discussed puzzle about WoW?how is overcoming it possible? We explain some of the ways in which previously weak-willed agents manage to overcome their weakness. Some of these are relatively straightforward?as agents learn of (...) the real costs of weakness, or as those costs mount dramatically, they can become strongly motivated to do what they already judged best. But other cases are more difficult to explain: sometimes, agents with a long history of forming and then weakly abandoning resolutions manage to stick to their guns. We argue that these cases can be explained by combining George Ainslie's model of agents as multiple preference orderings competing in game theoretic interactions along with the insights of evolutionary game theory. This can explain the puzzling cases where agents suddenly adopt successful strategies for avoiding weak-willed behavior, especially where agents gain no new information about themselves or the consequences of their actions. (shrink)

A powerful idea put forward in the recent philosophy of science literature is that scientific models are best understood as instruments, tools or, more generally, artifacts. This idea has thus far been developed in combination with the more traditional representational approach: accordingly, current artifactualist accounts treat models as representational tools. But artifactualism and representationalism are independent views, and adopting one does not require acceptance of the other. This paper argues that a leaner version of artifactualism, free of representationalist assumptions, is (...) both desirable and viable. Taking seriously the idea that models are artifacts can help us philosophically to make sense of how and why scientific modeling works even without reference to representation. (shrink)

The paper discusses the recent literature on abstraction/idealization in connection with the “paradox of infinite idealization.” We use the case of taking thermodynamics limit in dealing with the phenomena of phase transition and critical phenomena to broach the subject. We then argue that the method of infinite idealization is widely used in the practice of science, and not all uses of the method are the same. We then confront the compatibility problem of infinite idealization with scientific realism. We propose and (...) defend a contextualist position for realism and argue that the cases for infinite idealization appear to be fully compatible with contextual realism. (shrink)