Imagination seems to play an epistemic role in philosophical and scientific thought experiments, mindreading, and ordinary practical deliberations insofar as it generates new knowledge of contingent facts about the world. However, it also seems that imagination is limited to creative generation of ideas. Sometimes we imagine fanciful ideas that depart freely from reality. The conjunction of these claims is what I call the puzzle of knowledge through imagination. This chapter aims to resolve this puzzle. I argue that imagination has an (...) epistemic role to play, but it is limited to the context of discovery. Imagination generates ideas, but other cognitive capacities must be employed to evaluate these ideas in order for them to count as knowledge. Consideration of the Simulation Theory's so-called "threat of collapse” provides further evidence that imagination does not, on its own, yield new knowledge of contingent facts, and it suggests a way to supplement imagination in order to get such knowledge. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

We outline a neo-Meinongian framework labeled as Modal Meinongian Metaphysics (MMM) to account for the ontology and semantics of fictional discourse. Several competing accounts of fictional objects are originated by the fact that our talking of them mirrors incoherent intuitions: mainstream theories of fiction privilege some such intuitions, but are forced to account for others via complicated paraphrases of the relevant sentences. An ideal theory should resort to as few paraphrases as possible. In Sect. 1, we make this explicit via (...) two methodological principles, called the Minimal Revision and the Acceptability Constraint. In Sect. 2, we introduce the standard distinction between internal and external fictional discourse. In Sects. 3–5, we discuss the approaches of (traditional) Meinongianism, Fictionalism, and Realism—and their main troubles. In Sect. 6 we propose our MMM approach. This is based upon (1) a modal semantics including impossible worlds (Subsect. 6.1); (2) a qualified Comprehension Principle for objects (Subsect. 6.2); (3) a notion of existence-entailment for properties (Subsect. 6.3). In Sect. 7 we present a formal semantics for MMM based upon a representation operator. And in Sect. 8 we have a look at how MMM solves the problems of the three aforementioned theories. (shrink)

It is advisable to treat some sorts of discourse about fiction with the aid of an intensional operator "in such-And-Such fiction...." the operator may appear either explicitly or tacitly. It may be analyzed in terms of similarity of worlds, As follows: "in the fiction f, A" means that a is true in those of the worlds where f is told as known fact rather than fiction that differ least from our world, Or from the belief worlds of the community in (...) which the fiction originated. (shrink)

By a `denoting phrase' I mean a phrase such as any one of the following: a man, some man, any man, every man, all men, the present King of England, the present King of France, the center of mass of the solar system at the first instant of the twentieth century, the revolution of the earth round the sun, the revolution of the sun round the earth. Thus a phrase is denoting solely in virtue of its form. We may distinguish (...) three cases: (1) A phrase may be denoting, and yet not denote anything; e.g., `the present King of France'. (2) A phrase may denote one definite object; e.g., `the present King of England' denotes a certain man. (3) A phrase may denote ambiguously; e.g. `a man' denotes not many men, but an ambiguous man. The interpretation of such phrases is a matter of considerably difficulty; indeed, it is very hard to frame any theory not susceptible of formal refutation. All the difficulties with which I am acquainted are met, so far as I can discover, by the theory which I am about to explain. (shrink)

Models are of central importance in many scientific contexts. The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models). Scientists spend significant amounts of time building, (...) testing, comparing, and revising models, and much journal space is dedicated to interpreting and discussing the implications of models. In short, models are one of the principal instruments of modern science. (shrink)

Defined narrowly, epistemology is the study of knowledge and justified belief. As the study of knowledge, epistemology is concerned with the following questions: What are the necessary and sufficient conditions of knowledge? What are its sources? What is its structure, and what are its limits? As the study of justified belief, epistemology aims to answer questions such as: How we are to understand the concept of justification? What makes justified beliefs justified? Is justification internal or external to one's own mind? (...) Understood more broadly, epistemology is about issues having to do with the creation and dissemination of knowledge in particular areas of inquiry. This article will provide a systematic overview of the problems that the questions above raise and focus in some depth on issues relating to the structure and the limits of knowledge and justification. (shrink)

In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, I demonstrate (...) an important advantage my account has over other theories of scientific representation. All existing theories analyse scientific representation in terms of relations, such as similarity or denotation. By contrast, my account does not take representation in modelling to be essentially relational. For this reason, it can accommodate a group of models often ignored in discussions of scientific representation, namely models which are representational but which represent no actual object. (shrink)

It is argued that a number of important, and seemingly disparate, types of representation are species of a single relation, here called structural representation, that can be described in detail and studied in a way that is of considerable philosophical interest. A structural representation depends on the existence of a common structure between a representation and that which it represents, and it is important because it allows us to reason directly about the representation in order to draw conclusions about the (...) phenomenon that it depicts. The present goal is to give a general and precise account of structural representation, then to use that account to illuminate several problems of current philosophical interest — including some that do not initially seem to involve representation at all. In particular, it is argued that ontological reductions (like that of the natural numbers to sets), compositional accounts of semantics, several important sorts of mental representation, and (perhaps) possible worlds semantics for intensional logics are all species of structural representation and are fruitfully studied in the framework developed here. (shrink)

John Stuart Mill (1843) thought that proper names denote individuals and do not connote attributes. Contemporary Millians agree, in spirit. We hold that the semantic content of a proper name is simply its referent. We also think that the semantic content of a declarative sentence is a Russellian structured proposition whose constituents are the semantic contents of the sentence’s constituents. This proposition is what the sentence semantically expresses. Therefore, we think that sentences containing proper names semantically express singular propositions, which (...) are propositions having individuals as constituents. For instance, the sentence ‘George W. Bush is human’ semantically expresses a proposition that has Bush himself as a constituent. Call this theory Millianism. Many philosophers initially find Millianism quite appealing, but find it much less so after considering its many apparent problems. Among these problems are those raised by non-referring names, which are sometimes (tendentiously) called empty names. Plausible examples of empty names include certain names from fiction, such as ‘Sherlock Holmes’, which I shall call fictional names, and certain names from myth and false scientific theory, such as ‘Pegasus’ and ‘Vulcan’, which I shall call mythical names. I have defended Millianism from objections concerning empty names in previous work (Braun 1993). In this paper, I shall re-present those objections, along with some new ones. I shall then describe my previous Millian theory of empty names, and my previous replies to the objections, and consider whether the theory or replies need revision. I shall next consider whether fictional and mythical names are really empty. I shall argue that at least some utterances of mythical names are. (shrink)

The purpose of this paper is to suggest that models in scientific practice can be conceived of as epistemic artifacts. Approaching models this way accommodates many such things that working scientists themselves call models but that the semantic conception of models does not duly recognize as such. That models are epistemic artifacts implies, firstly, that they cannot be understood apart from purposeful human activity; secondly, that they are somehow materialized inhabitants of the intersubjective field of that activity; and thirdly, that (...) they can function also as knowledge objects. We argue that models as epistemic artifacts provide knowledge in many other ways than just via direct representative links. To substantiate our view we use a language‐technological artifact, a parser, as an example. (shrink)

A general account of modeling in physics is proposed. Modeling is shown to involve three components: denotation, demonstration, and interpretation. Elements of the physical world are denoted by elements of the model; the model possesses an internal dynamic that allows us to demonstrate theoretical conclusions; these in turn need to be interpreted if we are to make predictions. The DDI account can be readily extended in ways that correspond to different aspects of scientific practice.

In this paper, I develop Mauricio Suárez’s distinction between denotation, epistemic representation, and faithful epistemic representation. I then outline an interpretational account of epistemic representation, according to which a vehicle represents a target for a certain user if and only if the user adopts an interpretation of the vehicle in terms of the target, which would allow them to perform valid (but not necessarily sound) surrogative inferences from the model to the system. The main difference between the interpretational conception I (...) defend here and Suárez’s inferential conception is that the interpretational account is a substantial account—interpretation is not just a “symptom” of representation; it is what makes something an epistemic representation of a something else. (shrink)

How do models represent reality? There are two conditions that scientific models must satisfy to be representations of real systems, the aboutness condition and the epistemic condition. In this article, I critically assess the two main fictionalist theories of models as representations, the indirect fiction view and the direct fiction view, with respect to these conditions. And I develop a novel proposal, what I call ‘the new fiction view of models’. On this view, models are akin to fictional stories; they (...) represent real-world phenomena if they stand in a denotation relation with reality; and they enable knowledge of reality via the generation of theoretical hypotheses, model–world comparisons and direct attributions. (shrink)

A good many models used in physics and economics offer descriptions of imaginary situations, using a combination of mathematics and natural language. The descriptions are both thin - not much about the situation is filled in - and unrealistic - what is filled in is not true of many real situations. Yet we want to use the results of these models to inform our conclusions about a range of actually occurring situations. I propose we interpret many of these models as (...) fables. The actual happenings in the model are only one concrete instantiation of a lesson that is more widely applicable ‘when expressed in more abstract language.' A fable generally comes with the abstract lesson attached; parables, by contrast, usually require an interpretation from outside. Models, then, tend to be more like parables than fables. The right abstract interpretation is not supplied by the model itself. The central problem, then, is where shall it come from? (shrink)

This important book provides a theory about the nature of fiction, and about the relation between the author, the reader and the fictional text. The approach is philosophical: that is to say, the author offers an account of key concepts such as fictional truth, fictional characters, and fiction itself. The book argues that the concept of fiction can be explained partly in terms of communicative intentions, partly in terms of a condition which excludes relations of counterfactual dependence between the world (...) and the text. This communicative model is then applied to the following problems: how can something be 'true in the story' without being explicitly stated in the text? In what ways does interpreting a fictional story depend upon grasping its author's intentions? Is there always a unique best interpretation of a fictional text? What is the correct semantics for fictional names? What is the nature of our emotional response to a fictional work? In answering these questions the author explores the complex interaction between author, reader, and text. This interaction requires the reader to construct a 'fictional author' - a character in the story whose personality, beliefs and emotional states must be interpreted if the reader is to grasp the meaning of the work. (shrink)

In this book, Sorensen presents the first general theory of the thought experiment. He analyses a wide variety of thought experiments, ranging from aesthetics to zoology, and explores what thought experiments are, how they work, and what their positive and negative aspects are. Sorensen also sets his theory within an evolutionary framework and integrates recent advances in experimental psychology and the history of science.

I argue that judgments of what is ‘true in a fiction’ presuppose the Reality Assumption: the assumption that everything that is true is fictionally the case, unless excluded by the work. By contrast with the more familiar Reality Principle, the Reality Assumption is not a rule for inferring implied content from what is explicit. Instead, it provides an array of real-world truths that can be used in such inferences. I claim that the Reality Assumption is essential to our ability to (...) understand stories, drawing on a range of empirical evidence that demonstrates our reliance on it in narrative comprehension. However, the Reality Assumption has several unintuitive consequences, not least that what is fictionally the case includes countless facts that neither authors nor readers could ever consider. I argue that such consequences provide no reason to reject the Reality Assumption. I conclude that we should take fictions, like non-fictions, to be about the real world. (shrink)

Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In this paper I argue that models share important aspects in common with literary fiction, and that therefore theories of fiction can be brought to bear on these questions. In particular, I argue that the pretence theory as developed by Walton (1990, Mimesis as make-believe: on the foundations of the (...) representational arts. Harvard University Press, Cambridge/MA) has the resources to answer these questions. I introduce this account, outline the answers that it offers, and develop a general picture of scientific modelling based on it. (shrink)

Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...) Pauling's work involved modeling; much of Darwin's and Mendeleev's did not. In order to capture this distinction, I consider two examples of theory construction in detail: Volterra's treatment of post-WWI fishery dynamics and Mendeleev's construction of the periodic system. I argue that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis. This differentiation between modelers and non-modelers is one component of the larger project of understanding the practice of modeling, its distinctive features, and the strategies of abstraction and idealization it employs. (shrink)

Non-actual model systems discussed in scientific theories are compared to fictions in literature. This comparison may help with the understanding of similarity relations between models and real-world target systems. The ontological problems surrounding fictions in science may be particularly difficult, however. A comparison is also made to ontological problems that arise in the philosophy of mathematics.

entry for the Entry for the Stanford Encyclopedia of Philosophy, 2007.

This paper defends an inferential conception of scientific representation. It approaches the notion of representation in a deflationary spirit, and minimally characterizes the concept as it appears in science by means of two necessary conditions: its essential directionality and its capacity to allow surrogate reasoning and inference. The conception is defended by showing that it successfully meets the objections that make its competitors, such as isomorphism and similarity, untenable. In addition the inferential conception captures the objectivity of the cognitive representations (...) used by science, it sheds light on their truth and completeness, and it explains the source of the analogy between scientific and artistic modes of representation. (shrink)

... 112 ROBERT STALNAKER example Alvin Plantinga and Robert Adams) define possible worlds in terms of states of affairs or propositions ; others (for example Max Cresswell) use a strategy quite similar to that of situation semantics, defining possible worlds as constructs out of ..

The everyday capacity to understand the mind, or 'mindreading', plays an enormous role in our ordinary lives. Shaun Nichols and Stephen Stich provide a detailed and integrated account of the intricate web of mental components underlying this fascinating and multifarious skill. The imagination, they argue, is essential to understanding others, and there are special cognitive mechanisms for understanding oneself. The account that emerges has broad implications for longstanding philosophical debates over the status of folk psychology. Mindreading is another trailblazing volume (...) in the prestigious interdisciplinary Oxford Cognitive Science series. (shrink)

How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural (...) context of the problem; and dynamic processes of reasoning that extend ordinary cognition. Focusing on the third factor, Nersessian draws on cognitive science research and historical accounts of scientific practices to show how scientific and ordinary cognition lie on a continuum, and how problem-solving practices in one illuminate practices in the other. (shrink)

A striking feature of the traditional armchair method of philosophy is the use of imaginary examples: for instance, of Gettier cases as counterexamples to the justified true belief analysis of knowledge. The use of such examples is often thought to involve some sort of a priori rational intuition, which crude rationalists regard as a virtue and crude empiricists as a vice. It is argued here that, on the contrary, what is involved is simply an application of our general cognitive capacity (...) to handle counterfactual conditionals, which is not exclusively a priori and is not usefully conceived as a form of rational intuition. It is explained how questions of metaphysical possibility and necessity are equivalent to questions about counterfactuals, and the epistemology of the former (in particular, the role of conceiving or imagining) is a special case of the epistemology of the latter. A non-imaginary Gettier case is presented in order to show how little difference it makes. (shrink)

Call a bit of scientific discourse a description of a missing system when (i) it has the surface appearance of an accurate description of an actual, concrete system (or kind of system) from the domain of inquiry, but (ii) there are no actual, concrete systems in the world around us fitting the description it contains, and (iii) that fact is recognised from the outset by competent practitioners of the scientific discipline in question. Scientific textbooks, classroom lectures, and journal articles abound (...) with such passages; and there is a widespread practice of talking and thinking as though there are systems which fit the descriptions they contain perfectly, despite the recognition that no actual, concrete systems do so—call this the face value practice. There are, furthermore, many instances in which philosophers engage in the face value practice whilst offering answers to epistemological and methodological questions about the sciences. Three questions, then: (1) How should we interpret descriptions of missing systems? (2) How should we make sense of the face value practice? (3) Is there a set of plausible answers to (1) and (2) which legitimates reliance on the face value practice in our philosophical work, and can support the weight of the accounts which are entangled with that practice? In this paper I address these questions by considering three answers to the first: that descriptions of missing systems are straightforward descriptions of abstract objects, that they are indirect descriptions of “property-containing” abstracta, and that they are (in a different way) indirect descriptions of mathematical structures. All three proposals are present in the literature, but I find them wanting. The result is to highlight the importance of developing a satisfactory understanding of descriptions of missing systems and the face value practice, to put pressure on philosophical accounts which rely on the practice, and to help us assess the viability of certain approaches to thinking about models, theory structure, and scientific representation. (shrink)

This paper asks how, in science in general and in economics in particular, theoretical models aid the understanding of real-world phenomena. Using specific models in economics and biology as test cases, it considers three alternative answers: that models are tools for isolating the ‘capacities’ of causal factors in the real world; that modelling is ‘conceptual exploration’ which ultimately contributes to the development of genuinely explanatory theories; and that models are credible counterfactual worlds from which inductive inferences can be made. The (...) paper argues that the ‘credible worlds’ account captures significant aspects of scientific practice, even if many modellers see their work as conceptual exploration. (shrink)

How do scientific models represent in a way that enables us to discover new truths about reality and draw inferences about it? Contemporary accounts of scientific discovery answer this question by focusing on the cognitive mechanisms involved in the generation of new ideas and concepts in terms of a special sort of reasoning—or model-based reasoning—involving imagery. Alternatively, I argue that answering this question requires that we recognise the crucial role of the propositional imagination in the construction and development of models (...) for the purpose of generating hypotheses that are plausible candidates for truth. I propose simple fictionalism as a new account of models as Waltonian games of make-believe and suggest that models can lead to genuine scientific discovery when they are used as representations that denote real world phenomena and generate two main kinds of theoretical hypotheses, model-world comparisons and direct attributions. (shrink)

Recent cognitive accounts of the imagination propose that imagining and believing are in the same “code”. According to the single code hypothesis, cognitive mechanisms that can take input from both imagining and from believing will process imagination-based inputs (“pretense representations”) and isomorphic beliefs in much the same way. In this paper, I argue that the single code hypothesis provides a unified and independently motivated explanation for a wide range of puzzles surrounding fiction.

Utterances within the context of telling fictional tales that appear to be assertions are nevertheless not to be taken at face value. The present paper attempts to explain exactly what such 'pseudo-assertions' are, and how they behave. Many pseudo-assertions can take on multiple roles, both within fictions and in what I call 'participatory criticism' of a fiction, especially when they occur discourse-initially. This fact, taken together with problems for replacement accounts of pseudo-assertion based on the implicit prefixing of an 'in (...) the fiction' operator, suggest that pseudo-assertion is best understood as a kind of make-believe. This proposal is elaborated and defended, and some applications to fictionalism are tentatively explored. (shrink)

What are theoretical models and how do they contribute to a scientific understanding of reality? In this chapter, I will argue that models are akin to fictional stories in that they are human-made artifacts created through the imaginative activities of scientists. And I will suggest that the sort of imagination involved in modeling is make-believe and that this is constrained in three main ways which, together, enable knowledge of reality. I will conclude by addressing recent criticisms against the fiction view (...) of models and the relevance of scientific imagination in modeling put forward by Weisberg and Knuuttila. (shrink)

A good many models used in physics and economics offer descriptions of imaginary situations, using a combination of mathematics and natural language. The descriptions are both thin - not much about the situation is filled in - and unrealistic - what is filled in is not true of many real situations. Yet we want to use the results of these models to inform our conclusions about a range of actually occurring situations. I propose we interpret many of these models as (...) fables. The actual happenings in the model are only one concrete instantiation of a lesson that is more widely applicable ‘when expressed in more abstract language.' A fable generally comes with the abstract lesson attached; parables, by contrast, usually require an interpretation from outside. Models, then, tend to be more like parables than fables. The right abstract interpretation is not supplied by the model itself. The central problem, then, is where shall it come from? (shrink)