Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit with data and (...) on the aspects of a phenomenon that are modelled. Model users weigh the propositions entailed by a model and from this decide which of these propositions are crucial to the acceptance and continued use of the model. Thus, models represent phenomena when certain propositions they entail are true, but this alone does not exhaust the representational relationship. Therefore, the constraints that produce the choice of the relevant propositions in a model must also be examined and their analysis contributes to understanding the relationship between models and phenomena. (shrink)

Putnam's ``model-theoretic'' argument against metaphysical realism presupposes that an ideal scientific theory is expressible in a first order language. The central aim of this paper is to show that Putnam's ``first orderization'' of science, although unchallenged by numerous critics, makes his argument unsound even for adequate theories, never mind an ideal one. To this end, I will argue that quantitative theories, which dominate the natural sciences, can be adequately interpreted and evaluated only with the help of so-called theories of measurement (...) whose epistemological and methodological purpose is to justify systematic assignments of quantitative values to objects in the world. And, in order to fulfill this purpose, theories of measurement must have an essentially higher order logical structure. As a result, Putnam's argument fails because much of science turns out to rest on essentially higher order theoretical assumptions about the world. (shrink)

In this paper, I take scientific models to be epistemic representations of their target systems. I define an epistemic representation to be a tool for gaining information about its target system and argue that a vehicle’s capacity to provide specific information about its target system—its informativeness—is an essential feature of this kind of representation. I draw an analogy to our ordinary notion of interpretation to show that a user’s aim of faithfully representing the target system is necessary for securing this (...) feature. (shrink)

Scientific concepts, laws, theories, models and thought experiments are representations but uniquely different. In On Scientific Representation each is given a full philosophical exploration within an original, coherent philosophical framework that is strongly rooted in the Kantian tradition (Kant, Hertz, Vaihinger, Cassirer). Through a revisionist historical approach, Boniolo shows how the Kantian tradition can help us renew and rethink contemporary issues in epistemology and the philosophy of science.

An account of scientific representation in terms of partial structures and partial morphisms is further developed. It is argued that the account addresses a variety of difficulties and challenges that have recently been raised against such formal accounts of representation. This allows some useful parallels between representation in science and art to be drawn, particularly with regard to apparently inconsistent representations. These parallels suggest that a unitary account of scientific and artistic representation is possible, and our article can be viewed (...) as laying the groundwork for such an account—although, as we shall acknowledge, significant differences exist between these two forms of representation. (shrink)

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.

Realists regarding scientific knowledge – those who think that our best scientific representations truly describe both observable and unobservable aspects of the natural world – have special need of a notion of approximate truth. Since theories and models are rarely considered true simpliciter, the realist requires some means of making sense of the claim that they may be false and yet close to the truth, and increasingly so over time. In this paper, I suggest that traditional approaches to approximate truth (...) are insensitive to two crucial features of scientific knowledge, and that for each of these, analogies between representational practices in the sciences and in art prove useful to understanding how this situation can be remedied. First, I outline two distinct ways in which representations deviate from the truth, commonly referred to as ‘abstraction’ and ‘idealization’. Second, I argue that these practices exemplify different conventions of representation, and that for each, the conditions of approximation relevant to explicating the concept of approximate truth must be understood differently. The concept is thus heterogeneous; approximate truth is a virtue that is multiply realized, relative to different contexts of representation. This understanding is facilitated, I suggest, by considering the distinction between realistic and non-realistic representation in art. (shrink)

Recent work in the philosophy of science has generated an apparent conflict between theories attempting to explicate the nature of scientific representation. On one side, there are what one might call ‘informational’ views, which emphasize objective relations (such as similarity, isomorphism, and homomorphism) between representations (theories, models, simulations, diagrams, etc.) and their target systems. On the other side, there are what one might call ‘functional’ views, which emphasize cognitive activities performed in connection with these targets, such as interpretation and inference. (...) The main sources of the impression of conflict here are arguments by some functionalists to the effect that informational theories are flawed: it is suggested that relations typically championed by informational theories are neither necessary nor sufficient for scientific representation, and that any theory excluding functions is inadequate. In this paper I critically examine these arguments, and contend that, as it turns out, informational and functional theories are importantly complementary. (shrink)

In this paper, I consider how different versions of the similarity account of scientific representation might apply to a simple case of scientific representation, in which a model is used to predict the behaviour of a system. I will argue that the similarity account is potentially susceptible to the problem of accidental similarities between the model and the system and that, if it is to avoid this problem, one has to specify which similarities have to hold between a model and (...) a system for the model to be a faithful representation of that system. The sort of similarity that needs to hold between the model and the system, I argue, is a “second-order” similarity rather than simply a “first-order” similarity. This will not only avoid the problem but hopefully will contribute to dispelling the impression that an account of representation based on similarity is hopelessly vague. (shrink)

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. (shrink)

My two daughters would love to go tobogganing down the hill by themselves, but they are just toddlers and I am an apprehensive parent, so, before letting them do so, I want to ensure that the toboggan won’t go too fast. But how fast will it go? One way to try to answer this question would be to tackle the problem head on. Since my daughters and their toboggan are initially at rest, according to classical mechanics, their final velocity will (...) be determined by the forces they will be subjected to between the moment the toboggan will be released at the top of the hill and the moment it will reach its highest speed. The problem is that, throughout their downhill journey, my daughters and the toboggan will be subjected to an incredibly large number of forces—from the gravitational pull of any massive object in the universe to the weight of the snowflake that is sitting on the tip of one of my youngest daughter’s hairs—so that any attempt to apply the theory directly to the real-world system in all its complexity seems to be doomed to failure. (shrink)

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. (shrink)

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)

Recent discussions of the nature of representation in science have tended to import pre-established decompositions from analyses of representation in the arts, language, cognition and so forth. Which of these analyses one favours will depend on how one conceives of theories in the first place. If one thinks of them in terms of an axiomatised set of logico-linguistic statements, then one might be naturally drawn to accounts of linguistic representation in which notions of denotation, for example, feature prominently. If, on (...) the other hand, one conceives of theories in non-linguistic terms, as in the model-theoretic approach, then one might look to analyses of representation in the arts where notions of resemblance tend to be brought to the fore. Thus van Fraassen, for example, has imported such an analysis into his discussion of representation in science and argued that an appropriate account of resemblance can be given in terms of the set-theoretic relation of isomorphism. This has been strongly criticised by Suarez, who argues that just as isomorphism cannot capture representation in art, so it is inappropriate in the scientific context as well. Similarly Hughes draws on Goodman`s rejection of resemblance in art in favour of denotation and, rather confusingly perhaps, favours the latter whilst also maintaining the model-theoretic view of theories. In this paper, I shall examine the debate in terms of four claims: 1. Isomorphism is not sufficient for representation; 2. Isomorphism is not necessary for representation; 3. Models represent but theories do not; 4. Models denote and do not resemble. Each of these claims will be questioned and I will conclude by suggesting that, through appropriate modifications, a form of isomorphism can serve to underpin representation in both the arts and science. (shrink)

A one volume reference guide To The latest research in Philosophy of Science, written by an international team of leading scholars in the field.

The central concern of this article is whether the semantic approach has the resources to appropriately capture the core tenets of structural realism. Chakravartty (2001) has argued that a realist notion of correspondence cannot be accommodated without introducing a linguistic component, which undermines the approach itself. We suggest that this worry can be addressed by an appropriate understanding of the role of language in this context. The real challenge, however, is how to incorporate the core notion of `explanatory approximate truth' (...) in such a way that the emphasis on structure is retained. (shrink)

Scientific discourse is rife with passages that appear to be ordinary descriptions of systems of interest in a particular discipline. Equally, the pages of textbooks and journals are filled with discussions of the properties and the behavior of those systems. Students of mechanics investigate at length the dynamical properties of a system consisting of two or three spinning spheres with homogenous mass distributions gravitationally interacting only with each other. Population biologists study the evolution of one species procreating at a constant (...) rate in an isolated ecosystem. And when studying the exchange of goods, economists consider a situation in which there are only two goods, two perfectly rational agents, no restrictions on available information, no transaction costs, no money, and dealings are done immediately. Their surface structure notwithstanding, no competent scientist would mistake descriptions of such systems as descriptions of an actual system: we know very well that there are no such systems. These descriptions are descriptions of a model-system, and scientists use model-systems to represent parts or aspects of the world they are interested in. Following common practice, I refer to those parts or aspects as target-systems. What are we to make of this? Is discourse about such models merely a picturesque and ultimately dispensable façon de parler? This was the view of some early twentieth century philosophers. Duhem (1906) famously guarded against confusing model building with scientific theorizing and argued that model building has no real place in science, beyond a minor heuristic role. The aim of science was, instead, to construct theories, with theories understood as classificatory or representative structures systematically presented and formulated in precise symbolic.. (shrink)

The present paper argues that ‘mature mathematical formalisms’ play a central role in achieving representation via scientific models. A close discussion of two contemporary accounts of how mathematical models apply—the DDI account (according to which representation depends on the successful interplay of denotation, demonstration and interpretation) and the ‘matching model’ account—reveals shortcomings of each, which, it is argued, suggests that scientific representation may be ineliminably heterogeneous in character. In order to achieve a degree of unification that is compatible with successful (...) representation, scientists often rely on the existence of a ‘mature mathematical formalism’, where the latter refers to a—mathematically formulated and physically interpreted—notational system of locally applicable rules that derive from (but need not be reducible to) fundamental theory. As mathematical formalisms undergo a process of elaboration, enrichment, and entrenchment, they come to embody theoretical, ontological, and methodological commitments and assumptions. Since these are enshrined in the formalism itself, they are no longer readily obvious to either the novice or the proficient user. At the same time as formalisms constrain what may be represented, they also function as inferential and interpretative resources. (shrink)

(No abstract is available for this citation).

This paper focuses on two methodological questions that arise from Plato’s account of collection and division. First, what place does the method of collection and division occupy in Plato’s account of philosophical inquiry? Second, do collection and division in fact constitute a formal “method” (as most scholars assume) or are they simply informal techniques that the philosopher has in her toolkit for accomplishing different philosophical tasks? I argue that Plato sees collection and division as useful tools for achieving two distinct (...) goals – generating real definitions and discovering the basic natural kinds of a given domain of knowledge – both of which occupy a preliminary stage in his account of philosophical inquiry. As to the second question, I claim that the evidence for seeing collection and division as a formal method is weak. Although Plato calls the procedure a technê and a methodos, he makes no real attempt to formalize it in any way. For Plato, collection and division do not constitute an algorithmic process that can be learned from a rule book. Instead the ability to collect and divide properly are skills that good dialecticians must acquire through the kind of hands-on training illustrated by the Sophist and Statesman. Whereas Aristotle insists on formal rules for making proper divisions, Plato seems to emphasize the need to recognize where the natural joints of the world are. In this sense, Plato’s Sophist and Statesman and Aristotle’s Topics and Analytics present two very different pictures of collection and division. (shrink)

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the (...) relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation. (shrink)

Scientific representation: A long journey from pragmatics to pragmatics Content Type Journal Article DOI 10.1007/s11016-010-9465-5 Authors James Ladyman, Department of Philosophy, University of Bristol, 9 Woodland Rd, Bristol, BS8 1TB UK Otávio Bueno, Department of Philosophy, University of Miami, Coral Gables, FL 33124, USA Mauricio Suárez, Department of Logic and Philosophy of Science, Complutense University of Madrid, 28040 Madrid, Spain Bas C. van Fraassen, Philosophy Department, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132, USA Journal Metascience Online (...) ISSN 1467-9981 Print ISSN 0815-0796. (shrink)

Marian Przełęcki’s semantics for the Received View is a good explication of Carnap’s position on the subject, anticipates many discussions and results from both proponents and opponents of the Received View, and can be the basis for a thriving research program.

This review is a critical discussion of three main claims in Debs and Redhead’s thought-provoking book Objectivity, Invariance, and Convention. These claims are: (i) Social acts impinge upon formal aspects of scientific representation; (ii) symmetries introduce the need for conventional choice; (iii) perspectival symmetry is a necessary and sufficient condition for objectivity, while symmetry simpliciter fails to be necessary.

In the following text we will consider the question whether pictures can be regarded as arguments or not. Obviously, classical philosophical approaches lead to a different opinion about this topic than our common sense intuitions, which are fostered by our usage of ordinary language. On the one hand, logicians defend the thesis that arguments are of a linguistic kind. On the other hand, there are everyday contexts where, nevertheless, it seems appropriate to ascribe pictures the status of arguments. It is (...) this apparent tension between the philosophical approach and the one resulting from our linguistic practices that we will analyze in the following text. Examples – both from the everyday as the scientific context – will help us to settle the apparent dissent between the philosophical and the linguistic point of view. In the end, the thesis will be defended that pictorial representations make an essential contribution to communicative acts of argumentation without being regarded as (integral parts of ) arguments themselves. (shrink)

The Marburg neo-Kantians argue that Hermann von Helmholtz's empiricist account of the a priori does not account for certain knowledge, since it is based on a psychological phenomenon, trust in the regularities of nature. They argue that Helmholtz's account raises the 'problem of validity' (Gueltigkeitsproblem): how to establish a warranted claim that observed regularities are based on actual relations. I reconstruct Heinrich Hertz's and Ludwig Wittgenstein's Bild theoretic answer to the problem of validity: that scientists and philosophers can depict the (...) necessary a priori constraints on states of affairs in a given system, and can establish whether these relations are actual relations in nature. The analysis of necessity within a system is a lasting contribution of the Bild theory. However, Hertz and Wittgenstein argue that the logical and mathematical sentences of a Bild are rules, tools for constructing relations, and the rules themselves are meaningless outside the theory. Carnap revises the argument for validity by attempting to give semantic rules for translation between frameworks. Russell and Quine object that pragmatics better accounts for the role of a priori reasoning in translating between frameworks. The conclusion of the tale, then, is a partial vindication of Helmholtz's original account. (shrink)

Making sense of modeling: beyond representation Content Type Journal Article Category Original paper in Philosophy of Science Pages 335-352 DOI 10.1007/s13194-011-0032-8 Authors Isabelle Peschard, Philosophy Department, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 3.

Reichenbach's Philosophy of Space and Time (1928) avoids most of the logical positivist pitfalls it is generally held to exemplify, notably both conventionalism and verificationism. To see why, we must appreciate that Reichenbach's interest lies in how mathematical structures can be used to describe reality, not in how words like 'distance' acquire meaning. Examination of his proposed "coordinative definition" of congruence shows that Reichenbach advocates a reductionist analysis of the relations figuring in physical geometry (contrary to common readings that attribute (...) to him a holistic conventionalism), while embracing a thoroughly holistic understanding of empirical confirmation (contrary to rival operationalist readings). (shrink)

Review of Bas Van Fraassen, Scientific Representation, Oxford University Press, 2008.

Science represents the phenomena and it does so by providing representations of nature with the phenomena at best as a part. Criteria of adequacy for a representation pertain to accuracy and truth; but that representation is selective and may require distortion even in the selected parameters is an old and familiar point, intimately related to the insight that representation is intentional with adequacy relative to its particular purpose. If we add to this that observation and measurement are perspectival and that (...) the appearances to be saved are the perspectival measurement outcomes, the question whether this "saving" is an explanatory relation in contemporary physics can provide a new focus for the realist/anti-realist debate. The Born rule and von Neumann's "collapse" postulate in quantum mechanics provide a telling case. (shrink)

Bas C. van Fraassen presents an original exploration of how we represent the world.

The paper deals with an intellectual and historical approach to the changing meanings of the term “model” in life sciences. The author 1st tries to understand how modeling has gradually spread over life sciences then he particularly focus on the birth of mathematical modeling in this field. This quite new practice offers new insights on the old debate concerning the mathematization of life sciences. Nowadays, through computers, mathematics not only analyze or quantify but model things: what does it mean? The (...) question turns out to be dramatic as far as digital simulation is concerned. That is the reason why he choosed to study a particular case: the history of the individual plant mathematical modeling. On this case, one may discern various epistemological standpoints that caused various reactions to the emergence of computer simulation, from the 50s to the 90s. The author shows that philosophical views often play a role in the history of sciences, especially in the choice of supposed proper mathematical formalisms. This will indicate that contemporary discourses tend to echo each other. That is the reason why he feels authorized to address the Foucault’s concept—épistémè—to denote these convergences between the scientific and the philosophical discourses. Finally, it is suggested that this épistémè gradually is changing because one can currently observe the emergence of a “graphical” thought through these simulation experiments, which tends to replace a more functionalist thought. (shrink)

Analytical categories of scientific cultures have typically been used both exclusively and universally. For instance, when /styles of scientific research/ are employed in attempts to understand and narrate science, styles alone are usually employed. This article is a thought experiment in interweaving categories. What would happen if rather than employ a single category, we instead investigated several categories simultaneously? What would we learn about the practices and theories, the agents and materials, and the political-technological impact of science if we analyzed (...) and applied styles (à la Hacking and Crombie), paradigms (à la Kuhn), and models (à la van Fraassen and Cartwright) simultaneously? I address these questions in general and for a specific case study: /a brief history of systematics/. (shrink)

The dangers of character reification for cladistic inference are explored. The identification and analysis of characters always involves theory-laden abstraction—there is no theory-free “view from nowhere.” Given theory-ladenness, and given a real world with actual objects and processes, how can we separate robustly real biological characters from uncritically reified characters? One way to avoid reification is through the employment of objectivity criteria that give us good methods for identifying robust primary homology statements. I identify six such criteria and explore each (...) with examples. Ultimately, it is important to minimize character reification, because poor character analysis leads to dismal cladograms, even when proper phylogenetic analysis is employed. Given the deep and systemic problems associated with character reification, it is ironic that philosophers have focused almost entirely on phylogenetic analysis and neglected character analysis. (shrink)

I motivate the concept of styles of scientific investigation, and differentiate two styles, formal and compositional. Styles are ways of doing scientific research. Radically different styles exist. I explore the possibility of the unification of biology and social science, as well as the possibility of unifying the two styles I identify. Recent attempts at unifying biology and social science have been premised almost exclusively on the formal style. Through the use of a historical example of defenders of compositional biological social (...) science, the Ecology Group at the University of Chicago from, roughly, the 1930s to the 1950s, I attempt to show the coherence and possibility, if not utility, of employing the compositional style to effect the synthesis of biology and social science. I also relate the efforts of the Ecology Group to those of investigators in the Sociology Department of the University of Chicago. In my conclusion, I discuss the usefulness both of employing the category of styles of scientific investigation in historical and philosophical studies of science, as well as the concept of compositionality in scientific studies. I end the paper with some tentative suggestions regarding the importance of compositionality for an analysis of human society. (shrink)