In recent decades, philosophers of science have devoted considerable efforts to understand what models represent. One popular position is that models represent fictional situations. Another position states that, though models often involve fictional elements, they represent real objects or scenarios. Though these two positions may seem to be incompatible, I believe it is possible to reconcile them. Using a threefold distinction between different signs proposed by Peirce, I develop an argument based on a proposal recently made by Kralemann and Lattman (...) (in Synthese 190:3397–3420, 2013) that shows that the two aforementioned positions can be reconciled by distinguishing different ways in which a model representation can be used. In particular, on the basis of Peirce’s distinction between icons, indices and symbols, I argue that models can sometimes function as icons, sometimes as indexes and sometimes as symbols, depending on the context in which they are considered and the use that they are developed for because they all have iconic, indexical and symbolic features. In addition, I show that conceiving models as signs enables us to develop an account of scientific representation that meets the main desiderata that Shech (in Synthese 192:3463–3485, 2015) presents. (shrink)

Philosophers of science have developed several accounts of how consideration of scientific models can prompt learning about real-world targets. In recent years, various authors advocated the thesis that consideration of so-called minimal models can prompt learning about such targets. In this paper, I draw on the philosophical literature on scientific modelling and on widely cited illustrations from economics and biology to argue that this thesis fails to withstand scrutiny. More specifically, I criticize leading proponents of such thesis for failing to (...) explicate in virtue of what properties or features minimal models supposedly prompt learning and for substantially overstating the epistemic import of minimal models. I then examine and refute several arguments one may put forward to demonstrate that consideration of minimal models can prompt learning about real-world targets. In doing so, I illustrate the implications of my critique for the wider debate on the epistemology of scientific modelling. (shrink)

In this essay I shall focus on the adoption of the Semantic Approach by structural realists, including myself, who have done so on the grounds that it wears its structuralist sympathies on its sleeve. Despite this, the SA has been identified as standing in tension with the ontological commitments of the so-called ’ontic’ form of this view and so I shall explore that tension before discussing the usefulness of the SA in framing scientific representation and concluding with a discussion of (...) the implications of the ontological status of theories and models themselves. (shrink)

The ontological status of theories themselves has recently re-emerged as a live topic in the philosophy of science. We consider whether a recent approach within the philosophy of art can shed some light on this issue. For many years philosophers of aesthetics have debated a paradox in the (meta)ontology of musical works (e.g. Levinson [1980]). Taken individually, there are good reasons to accept each of the following three propositions: (i) musical works are created; (ii) musical works are abstract objects; (iii) (...) abstract objects cannot be created. However it seems clear that, if one wants to avoid inconsistency, one cannot commit to all three. Following up recent developments courtesy of Cameron ([2008a]), we consider how one might respond to the corresponding set of propositions in the (meta)ontology of scientific theories. 1 Introduction2 Setting up the Problem3 What to Reject? 3.1 Scientific theories are not created? 3.2 Scientific theories are not abstract objects? 3.3 Abstract objects can be created?4 A Fourth Way: Truth-maker Theory5 Objections and Replies 5.1 What are the truth-makers? 5.2 Objections from World 3 5.3 Fictionalism 5.4 Concrete/abstract6 Conclusion. (shrink)

This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making (...) counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed. (shrink)

In this essay, I shall show that the so-called inferential (Suárez 2003 and 2004 ) and interpretational (Contessa 2007 ) accounts of scientific representation are respectively unsatisfactory and too weak to account for scientific representation ( pars destruens ). Along the way, I shall also argue that the pragmatic similarity (Giere 2004 and Giere 2010 ) and the partial isomorphism (da Costa and French 2003 and French 2003 ) accounts are unable to single out scientific representation. In the pars construens (...) I spell out a limiting case account which has explanatory surplus vis à vis the approaches which I have previously reviewed. My account offers an adequate treatment of scientific representation, or so I shall try to argue. Central to my account is the notion of a pragmatic limiting case, which will be characterized in due course. (shrink)

Several prominent philosophers of science, most notably Ron Giere, propose that scientific theories are collections of models and that models represent the objects of scientific study. Some, including Giere, argue that models represent in the same way that pictures represent. Aestheticians have brought the picturing relation under intense scrutiny and presented important arguments against the tenability of particular accounts of picturing. Many of these arguments from aesthetics can be used against accounts of representation in philosophy of science. I rely on (...) Dominic Lopes' recent summary of arguments against various views of picturing and reformulate some of them to fit the philosophy of science context. My specific targets here are Giere and Steven French. I go on to argue that assuming all scientific models and images represent in the same way is not the best guide to understanding scientific practice. (shrink)

In this contribution, I comment on Raffaella Campaner’s defense of explanatory pluralism in psychiatry (in this volume). In her paper, Campaner focuses primarily on explanatory pluralism in contrast to explanatory reductionism. Furthermore, she distinguishes between pluralists who consider pluralism to be a temporary state on the one hand and pluralists who consider it to be a persisting state on the other hand. I suggest that it would be helpful to distinguish more than those two versions of pluralism – different understandings (...) of explanatory pluralism both within philosophy of science and psychiatry – namely moderate/temporary pluralism, anything goes pluralism, isolationist pluralism, integrative pluralism and interactive pluralism. Next, I discuss the pros and cons of these different understandings of explanatory pluralism. Finally, I raise the question of how to implement or operationalize explanatory pluralism in scientific practice; how to structure the “genuine dialogue” or shape “the pluralistic attitude” Campaner is referring to. As tentative answers, I explore a question-based framework for explanatory pluralism as well as social-epistemological procedures for interaction among competing approaches and explanations. (shrink)

A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences about the world from (...) models. I present and critically assess two leading accounts of model assessment, arguing that neither is sufficient to provide a complete understanding of model evaluation. I introduce a more powerful framework incorporating elements of the two views, which can help answer these three questions: What is the target of evaluation in model assessment? How does that evaluation proceed? What licenses us in making inferences about the real world, based on the evaluation of our models as successful? The framework identifies two distinct targets of model evaluation: representational similarity between the model and target system, and the adequacy of the model as a tool to answer questions. Both assessments must be relativized to a purpose, of which there are three general kinds: descriptive, predictive, and explanatory. These purposes differ in the way they inform the similarity relation, which is relevant for the similarity assessment, and the output they produce, which is relevant for the adequacy assessment. Any model can be assessed relative to any purpose, however a model encodes certain decisions made during the model’s construction, which impact its ability to be applied to a new purpose or new domain. My framework shows that extending a model, and drawing inferences from it, depends on its representational similarity. I apply this framework to several examples taken from astrophysics showing in detail how it can help illuminate the structure of the models, as well as make the justification for inferences made from them clear. The final chapter is a detailed analysis of a contemporary debate surrounding the use of models in astrophysics, between proponents of MOND and the standard ΛCDM model. (shrink)

This paper is intended to sketch the definition of a methodological tool -- the notion of a format of representation -- for the study of scientific theorising. One of its main assumption is that a philosophical study of theorising needs to pay attention to other types of units of analysis than the traditional ones, namely, theories and models approached in a logical and structural way, since scientific reasoning is always led on concrete representational devices and depends upon their specific properties. (...) The notion of a format is intended to characterise the differences between various types of representational devices, in terms of the inferences they enable cognitive agents to draw. (shrink)

Starting from the sixties of the past century theory change has become a main concern of philosophy of science. Two of the best known formal accounts of theory change are the post-Popperian theories of verisimilitude (PPV for short) and the AGM theory of belief change (AGM for short). In this paper, we will investigate the conceptual relations between PPV and AGM and, in particular, we will ask whether the AGM rules for theory change are effective means for approaching the truth, (...) i.e., for achieving the cognitive aim of science pointed out by PPV. First, the key ideas of PPV and AGM and their application to a particular kind of propositional theories - the so called "conjunctive propositions" - will be illustrated. Afterwards, we will prove that, as far as conjunctive propositions are concerned, AGM belief change is an effective tool for approaching the truth. (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)

The central question of this thesis is how one can learn about particular targets by using models of those targets. A widespread assumption is that models have to be representative models in order to foster knowledge about targets. Thus the thesis begins by examining the concept of representation from an epistemic point of view and supports an account of representation that does not distinguish between representation simpliciter and adequate representation. Representation, understood in the sense of a representative model, is regarded (...) as a success term. That is, a representative model is one relatum in a relation of adequate representation (Chapter 2). When a representative model represents a target, it allows users of this model to learn something about the target. It is argued that a representative model has this epistemic function because it shares relevant features with the target. This presupposes a similarity view of representation. Similarity views of representation face serious objections, which will be rebutted (Chapter 3). One way of spelling out a similarity view of representation is to defend an indirect view of representation. In this thesis, which does not argue for an indirect view, it is assumed that the indirect view is a good option, if not the best, for articulating the similarity view. It is demonstrated how such an indirect view can be expanded to account for cases of technological modeling. A case study in bioengineering is used to show that the indirect view of representation must acknowledge a distinction between two directions of fit in relations between vehicles and targets. In this context the notion of design is interpreted as a relation between a vehicle and a target, thereby connecting ideas from philosophy of science with ideas from philosophy of technology (Chapter 4). Fictionalist accounts of models are intended to tackle the issue of the ontology of models. In this thesis, however, two prominent fictionalist accounts are discussed from an epistemological point of view in light of the central question regarding how one can learn about targets by using models. This question is addressed from the standpoint of Waltonian fictionalism. The result of the discussion is that the two discussed Waltonian fictionalist accounts cannot sufficiently answer the question. These accounts are criticized for their inability to deliver a satisfactory epistemology of representation (Chapter 5). Although Waltonian fictionalism is criticized, the present thesis also shows that the foundational theory of Waltonian fictionalism, the theory of make-believe can nevertheless be used to account for the distinction between projections and predictions that is made by the Intergovernmental Panel on Climate Change (Chapter 6). (shrink)

The years 1880-1914 were a time of intense experimentation in the visual arts. Representative conventions became variable, and artists deliberately departed from a concept of depiction considered as physical resemblance or photographic similarity. Visual representations progressed toward a conceptualization of figures and objects that transcended perceptual data, and the rendering of pictorial objects turned into an experiment involving complex visualization processes. This paper explores the interplay between artistic and scientific representative practices between 1880 and 1914. I argue that science and (...) technology acted as substantial challenges upon the concept of resemblance in art and that the rhythm of scientific and technological discoveries at the turn of the 20th century paralleled a shift from a notion of similarity to one of homomorphism in the conceptualization of pictorial representation. Homomorphism denotes representations which dispense with a point-to-point correspondence between depicted objects and perceptual data. I developed the concept from a scholarly study of Charles S. Peirce’s pragmatic account of representation, and in particular his theory of iconicity. Peirce defined iconic signs as “partaking in the character of the object” (CP 4.531), that is, as preserving the same relational structure as their object. A theory of iconicity as homomorphism successfully exemplifies representative relations based on structure preservation. Applied to 20th century representative practice, homomorphism offers a plausible explanation for representations in which a considerable conceptual effort is required, independently of a point-to-point correspondence between depicted objects and perceptual data. Using four case studies - the photographer Alfred Stieglitz and the painters André Derain, Max Weber and Pablo Picasso - I argue that representative practice between 1880 and 1914 was strongly informed by experimental scientific practices and that the shift from figurative to conceptual representation in art was triggered by a more significant theoretical shift involving representation as a general philosophical notion. Rather than a normative quest for the necessary and sufficient conditions for representation, I will propose a pragmatic evaluation of the means and strategies through which artists and scientists devise perspicuous and useful representations of the world. My analysis of the correlations between artistic and scientific representations at the turn of the 20th century aims to fulfill a twofold purpose. From a historical viewpoint, it draws significant parallels between the experimental aspects of representative practices in art and science considered as ways of exploring natural phenomena and intervening upon them. From a philosophical viewpoint, my goal is to propose a novel epistemological framework to assess how the shift in the conceptualization of representations affected subsequent styles of knowing and experimental practices in art and science. Ultimately, by combining the relative merits of historical and philosophical accounts of representation, I will argue for the advantages and desirability of a philosophically informed history of representative practice. (shrink)