In this paper we explore the constraints that our preferred account of scientific representation places on the ontology of scientific models. Pace the Direct Representation view associated with Arnon Levy and Adam Toon we argue that scientific models should be thought of as imagined systems, and clarify the relationship between imagination and representation.

Abstract: Many, if not most philosophers, deny that a sentence like ‘Sherlock Holmes smokes’ could be true. However, this attitude conflicts with the assignment of true to that sentence by natural language speakers. Furthermore, this process of assigning truth values to sentences like ‘Sherlock Holes smokes’ seems indistinguishable from the process that leads speakers to assign true to other sentences, those like ‘Bertrand Russell smokes’. I will explore the idea that when speakers assign the value true to the first sentence, (...) they are not mistaken or confused — that we ought to take these assignments at face value. I show how the most popular alternative to this idea is inadequate for explaining various sentences involving fictional names. In addition, I offer evidence that these truth value assignments to sentences are tracking semantic content rather than pragmatic effects. (shrink)

Fictional names present unique challenges for semantic theories of proper names, challenges strong enough to warrant an account of names different from the standard treatment. The theory developed in this paper is motivated by a puzzle that depends on four assumptions: our intuitive assessment of the truth values of certain sentences, the most straightforward treatment of their syntactic structure, semantic compositionality, and metaphysical scruples strong enough to rule out fictional entities, at least. It is shown that these four assumptions, taken (...) together, are inconsistent with referentialism, the common view that names are uniformly associated with ordinary individuals as their semantic value. Instead, the view presented here interprets names as context-sensitive expressions, associated in a context of utterance with a particular act of introduction, or dubbing, which is then used to determine their semantic value. Some dubbings are referential, which associate names with ordinary individuals as their semantic values; others are fictional, which associate names, instead, with sets of properties. Since the semantic values of names can be of different sorts, the semantic rule interpreting predication must be complex as well. In the body of the paper, I show how this new treatment of names allows us to solve our original puzzle. I defend the complexity of the semantic predication rule, and address additional worries about ontological commitment. (shrink)

Nelson Goodman's proposal for a reconception of meaning consists in replacing the absolute notion ofsameness of meaning by that oflikeness of meaning (with respect to pertinent contexts). According to this view, synonymy is a matter of degree (of interreplaceability) with identity of expression as a limiting case. Goodman's demonstration that no two expressions are exactly alike in meaning is shown to be unsuccessful. Although it does not make use of quotational contexts for the test of interreplaceability, it is tantamount to (...) their acceptance. Goodman rejects quotational contexts; I argue that they should be accepted. This move offers two advantages.Firstly, and mainly, it allows interlinguistic comparison of meaning, something that has not been deemed possible in the received version of Goodman's account.Secondly, it restores the full scale of likeness of meaning damaged by the renunciation of those contexts that guarantee difference in meaning for diverse expressions. (shrink)

This book is about whether reference to an individual is the essential feature of a proper name -- a widely held view -- or whether referring to an individual is simply a contingent feature. Three questions need resolving, then. First, whether all names in particular contexts are themselves referring devices. Second, whether recognizing names types and the consequent issue of their ambiguity can be resolved simply by distinguishing between name types and tokens thereof. Last, whether names are ever referential in (...) the way Kripke and others have convincingly argued. The answer to first two questions is negative. The answer to third is a qualified "yes." I explain the theory that allows for these answers in the manuscript, as well as addressing other issues such as: the problem of fictional names; descriptive names; empty names; what an act of naming consists of; an account of ontological commitment; and the data that suggests that names are predicates. (shrink)

In non-philosophical discourse, “identity” is often used when the specific character of artefacts is described or evaluated. We argue that this usage of “identity” can be explicated as referring to the symbol properties of artefacts as they are conceptualized in the symbol theory of Goodman and Elgin. This explication is backed by an analysis of various uses of “identity”. The explicandum clearly differs from the concepts of numerical identity, qualitative identity and essence, but it has a range of similarities with (...) the notion of self-concept used in psychology and practical philosophy. The proposed explication is used to analyse claims about identity-pluralism and identity-conflicts. Firstly, the explication allows us to distinguish various ways how the same artefact can have a plurality of identities. Secondly, more or less sharp conflicts within an identity or between identities of an artefact are distinguished. Thirdly, many phenomena called “identity-conflicts” are only apparently identity-conflicts and can be analysed as involving some other form of tension. (shrink)

Philosophical discussions of depiction sometimes suffer from a lack of differentiation between several questions concerning the nature of pictorial representation. To provide a suitable framework I distinguish six such questions and several levels on which one might want to proceed in order to answer some of them. With this background, I reconstruct Goodman's and Elgin's answer to the specific question: What distinguishes the pictorial from the verbal or linguistic? I try to reveal some major motivations behind their system-oriented approach and (...) to indicate some reasons why a strategy of this kind is to a certain extent mandatory to grasp the nature of the pictorial. The system-relative and functional character of depiction has to be captured by every adequate theory. (shrink)

Cognitive science uses the notion of computational information processing to explain cognitive information processing. Some philosophers have argued that anything can be described as doing computational information processing; if so, it is a vacuous notion for explanatory purposes.An attempt is made to explicate the notions of cognitive information processing and computational information processing and to specify the relationship between them. It is demonstrated that the resulting notion of computational information processing can only be realized in a restrictive class of dynamical (...) systems called physical notational systems (after Goodman's theory of notationality), and that the systems generally appealed to by cognitive science-physical symbol systems-are indeed such systems. Furthermore, it turns out that other alternative conceptions of computational information processing, Fodor's (1975) Language of Thought and Cummins' (1989) Interpretational Semantics appeal to substantially the same restrictive class of systems. (shrink)

Many scientific models are representations. Building on Goodman and Elgin’s notion of representation-as we analyse what this claim involves by providing a general definition of what makes something a scientific model, and formulating a novel account of how they represent. We call the result the DEKI account of representation, which offers a complex kind of representation involving an interplay of, denotation, exemplification, keying up of properties, and imputation. Throughout we focus on material models, and we illustrate our claims with the (...) Phillips-Newlyn machine. In the conclusion we suggest that, mutatis mutandis, the DEKI account can be carried over to other kinds of models, notably fictional and mathematical models. (shrink)

A shorthand symbolism for the relational mapping of categories is introduced and developed on the basis of Nelson Goodman's structural methodology. Through a reconstruction of extensional isomorphism that Goodman introduces as a criterion for definitional accuracy, and a brief reminder of the argument structure behind his ‘new riddle of induction’, Goodman's radical ontological relativism is turned into a protological principle of what I call ‘domain constituting philosophy’. MSS is demonstrated with reference to Goodman's symbol theory, particularly his notion of exemplification, (...) as well as in a final structured comparison of Frege's ‘sense’ with Goodman's straightforward construction of ‘secondary extension’. (shrink)

Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...) ideas that scientific models are ‘similar’, or structurally morphic, to their target systems. I argue that these approaches are misguided, and that at best these relationships concern the accuracy of a pre-existing representational relationship. I also pay particular attention to the sense in which target systems can be appropriately taken to exhibit a ‘structure’, and van Fraassen’s recent argument concerning the pragmatic equivalence between representing phenomena and data. My next target is the idea that models should not be seen as objects in their own right, but rather what look like descriptions of them are actually direct descriptions of target systems, albeit not ones that should be understood literally. I argue that these approaches fail to do justice to the practice of scientific modelling. Finally I turn to the idea that how models represent is grounded, in some sense, in their inferential capacity. I compare this approach to anti-representationalism in the philosophy of language and argue that analogous issues arise in the context of scientific representation. Part iii contains my positive proposal. I provide an account of scientific representation based on Goodman and Elgin’s notion of representation-as. The result is a highly conventional account which is the appropriate level of generality to capture all of its instances, whilst remaining informative about the notion. I illustrate it with reference to the Phillips-Newlyn machine, models of proteins, and the Lotka-Volterra model of predator-prey systems. These examples demonstrate how the account must be understood, and how it sheds light on our understanding of how models are used. I finally demonstrate how the account meets the desiderata laid out at the beginning of the thesis, and outline its implications for further questions from the philosophy of science; not limited to issues surrounding the applicability of mathematics, idealisation, and what it takes for a model to be ‘true’. (shrink)

Se considera que la ciencia es el espejo de la naturaleza, mientras que el arte imita la vida. De ser así, las representaciones en ambas disciplinas deberían asemejarse a sus objetos. En contra de tales teorías miméticas, argumento que la ejemplificación y no la simple semejanza es crucial. Explico en qué consiste la ejemplificación: una relación referencial de un ejemplar con alguna de sus características. Puesto que la ejemplificación es selectiva, un ejemplar puede diferir de su referente en aspectos no (...) ejemplificados. Ésta es la razón por la cual una idealización, que estrictamente es falsa, puede ofrecer comprensión del fenómeno que le concierne. A partir de analogías con las representaciones pictóricas, muestro cómo un modelo ejemplifica características que comparte con su objeto, pone de relieve la importancia de tales características y con ello proporciona comprensión del sistema en cuestión. (shrink)