Online research in philosophy

We propose that scientific representation is a special case of a more general notion of representation, and that the relatively well worked-out and plausible theories of the latter are directly applicable to thc scientific special case. Construing scientific representation in this way makes the so-called “problem of scientific representation” look much less interesting than it has seerned to many, and suggests that some of the (hotly contested) debates in the literature are concerned with non-issues.

In this paper I will defend a new account of scientific representation. I will begin by looking at the benefits and drawbacks of two recent accounts on scientific representation: Hughes’ DDI account and Suárez’ inferential account. Next I use some of Galileo’s models in the Discorsi as a heuristic tool for a better account of scientific representation. Next I will present my model. The main idea of my account, which I refer to as the pragmatic model of shared characteristics (PMSC), is that a model represents, if and only if, (1) a person accepts that there is a set of shared characteristics between the model and its target; (2) this set has the inferential power to generate results which can be tested empirically; (3) and the corresponding test(s) of these results is/are in agreement with our data and the specific cognitive goals we have in mind.

In this paper, I show how some of the fundamental problems that face a structuralist conception of representation can be solved by (a) distinguishing between three relevant senses of ‘representation’ (i.e. denotation, epistemic representation, and faithful epistemic representation), (b) claiming that, properly understood, the structural conception of representation aims at providing us with an account of faithful epistemic representation not of epistemic representation simpliciter, and (c) adopting an interpretational conception of epistemic representation.

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.

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.

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.

Today most philosophers of science believe that models play a central role in science and that one of the main functions of scientific models is to represent systems in the world. Despite much talk of models and representation, however, it is not yet clear what representation in this context amounts to nor what conditions a certain model needs to meet in order to be a representation of a certain system. In this thesis, I address these two questions. First, I will distinguish three senses in which something, a vehicle, can be said to be a representation of something else, a target—which I will call respectively denotation, epistemic representation, and faithful epistemic representation—and I will argue that the last two senses are the most important in this context. I will then outline a general account of what makes a vehicle an epistemic representation of a certain target for a certain user—which, according to the account I defend, is the fact that a user adopts what I call an interpretation of the vehicle in terms of the target—and of what makes an epistemic representation of a certain target a faithful epistemic representation of it—which, according to the account I defend, is a specific sort of structural similarity between the vehicle and the target.

I argue against theories that attempt to reduce scientific representation to similarity or isomorphism. These reductive theories aim to radically naturalize the notion of representation, since they treat scientist's purposes and intentions as non-essential to representation. I distinguish between the means and the constituents of representation, and I argue that similarity and isomorphism are common but not universal means of representation. I then present four other arguments to show that similarity and isomorphism are not the constituents of scientific representation. I finish by looking at the prospects for weakened versions of these theories, and I argue that only those that abandon the aim to radically naturalize scientific representation are likely to be successful.

The main aim of this paper is to disentangle three senses in which we can say that a model represents a system—denotation epistemic representation, and successful epistemic representation--and to individuate what questions arise from each sense of the notion of representation as used in this context. Also, I argue that a model is an epistemic representation of a system only if a user adopts a general interpretation of the model in terms of a system. In the process, I hope to clarify where those who, following Craig Callander and Jonathan Cohen, claim that there is no special problem about scientific representation go wrong. In the terminology adopted here, even if scientific representation is only an instance of epistemic representation, scientific representation should not be confounded with denotation.