In this paper I begin with a recent challenge to the Semantic Approach and identify an underlying assumption, namely that identity conditions for theories should be provided. Drawing on previous work, I suggest that this demand should be resisted and that the Semantic Approach should be seen as a philosophical device that we may use to represent certain features of scientific practice. Focussing on the partial structures variant of that approach, I then consider a further challenge that arises from a (...) concern with the role of idealisations in that practice. I argue that the partial structures approach is capable of meeting this challenge and I conclude with some broader observations about the role of such formal accounts within the philosophy of science. (shrink)

In this paper, we explore an under-investigated question concerning the class of formal models that aim at providing normative guidance. We call such models normative models. In particular, we examine the question of how normative models can successfully exert normative guidance. First, we highlight the absence of a discussion of this question – which is surprising given the extensive debate about the success conditions of descriptive models – and motivate its importance. Second, we introduce and discuss two potential accounts of (...) the success conditions of normative models. Our tentative conclusion is that the second account is more promising. (shrink)

In this paper, I utilise the growing literature on scientific modelling to investigate the nature of formal semantics from the perspective of the philosophy of science. Specifically, I incorporate the inferential framework proposed by Bueno and Colyvan : 345–374, 2011) in the philosophy of applied mathematics to offer an account of how formal semantics explains and models its data. This view produces a picture of formal semantic models as involving an embedded process of inference and representation applying indirectly to linguistic (...) phenomena. The final aim of the paper is directed at proposing a novel account of the syntax–semantics interface while shedding light on empty categories, semantically null forms, underspecified content and compositionality as a whole. (shrink)

I show that extant attempts to capture and generalize empirical adequacy in terms of partial structures fail. Indeed, the motivations for the generalizations in the partial structures approach are better met by the generalizations via approximation sets developed in “Generalizing Empirical Adequacy I”. Approximation sets also generalize partial structures.

During the second half of the nineteenth century, electronegativity has been one of the most relevant chemical concepts to explain the relationships between chemical substances and their possible reactions. Specifically, EN is a property of the substances that allows them to attract external electrons in bonding situations. The problem arises because EN cannot be measured directly. Indeed, the only way to measure it is through different properties that do can be directly measured, for instance enthalpy, ionization energies or electron affinities. (...) What is particularly troubling about this case in quantum chemistry is that the different models used to describe and quantify EN are incompatible but, in a certain sense, equivalent because the same EN scale results in all of them. By analyzing Linus Pauling’s and Robert Mulliken’s models of EN, it will be argued that, if we remain cling to a traditional representative conception of models, we cannot understand the meaning of the information provided by those models. Indeed, if we do not want to adopt an instrumentalist point of view concerning chemical knowledge, we should reconsider by virtue of what a model represents the system, or, in other words, which the factors that determine the representative power of a model are. I will propose a new perspective that incorporates the role of experimental techniques in the very notion of representation; this perspective allows us to understand how supposedly incompatible models of the same target system can be both simultaneously representative. (shrink)

Deep learning is a kind of machine learning which happens in a certain type of artificial neural networks called deep networks. Artificial deep networks, which exhibit many similarities with biological ones, have consistently shown human-like performance in many intelligent tasks. This poses the question whether this performance is caused by such similarities. After reviewing the structure and learning processes of artificial and biological neural networks, we outline two important reasons for the success of deep learning, namely the extraction of successively (...) higher level features and the multiple layer structure, which are closely related to each other. Then some indications about the framing of this heated debate are given. After that, an assessment of the value of artificial deep networks as models of the human brain is given from the similarity perspective of model representation. Finally, a new version of computational functionalism is proposed which addresses the specificity of deep neural computation better than classic, program based computational functionalism. (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)

The paper surveys Floridi’s attempt for laying down informational structural realism. After considering a number of reactions to the pars destruens of Floridi’s attack on the digital ontology, I show that Floridi’s enterprise for enriching the ISR by borrowing elements from the ontic form of structural realism is blighted by a haunting inconsistency. ISR has been originally developed by Floridi as a restricted and level dependent form of structural realism which remains mainly bonded within the borders of a Kantian perspective. (...) I argue that this perspective doesn’t mesh nicely with the ontic interpretation that Floridi attached to the ISR. I substantiate this claim through the assessment of Floridi’s strategy for reconciling the epistemic and ontic forms of the SR, as well as by close examination of his use of method of levels of abstraction and his notion of semantic information. My proposal is that the ISR could be defended best against the mentioned and similar objections by being interpreted as an extension of the epistemic SR. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. (shrink)

Wigner famously referred to the `unreasonable effectiveness' of mathematics in its application to science. Using Wigner's own application of group theory to nuclear physics, I hope to indicate that this effectiveness can be seen to be not so unreasonable if attention is paid to the various idealising moves undertaken. The overall framework for analysing this relationship between mathematics and physics is that of da Costa's partial structures programme.

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)

Philosophers have long been interested in a series of interrelated questions about natural kinds. What are they? What role do they play in science and metaphysics? How do they contribute to our epistemic projects? What categories count as natural kinds? And so on. Owing, perhaps, to different starting points and emphases, we now have at hand a variety of conceptions of natural kinds—some apparently better suited than others to accommodate a particular sort of inquiry. Even if coherent, this situation isn’t (...) ideal. My goal in this article is to begin to articulate a more general account of ‘natural kind phenomena’. While I do not claim that this account should satisfy everyone—it is built around a certain conception of the epistemic role of kinds and has an obvious pragmatic flavour—I believe that it has the resources to go further than extant alternatives, in particular the homeostatic property cluster view of kinds. (shrink)

This thesis offers a naturalist revision of Alain Badiou’s philosophy. This goal is pursued through an encounter of Badiou’s mathematical ontology and theory of truth with contemporary trends in philosophy of mathematics and philosophy of science. I take issue with Badiou’s inability to elucidate the link between the empirical and the ontological, and his residual reliance on a Heideggerian project of fundamental ontology, which undermines his own immanentist principles. I will argue for both a bottom-up naturalisation of Badiou’s philosophical approach (...) to mathematics and a top-down naturalisation. Articulating my particular understanding of what realism and naturalism should commit us to, I propose a creative fusion of Badiou’s attention to metamathematical results with a structural-informational metaphysics, proposing a ‘matherialism’ uniting the more daring speculative insights of the former with the naturalist and empiricist commitments motivating the latter. (shrink)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. 1 Introduction2 Biological Population, Broad and Narrow3 Difficulties with Narrow Biological Population Conditions3.1 Against the genealogical condition3.2 Against the conspecificity condition3.3 Against the proximity condition3.4 Against the typology condition4 Causal Connectivity5 Massively Multidimensional Population Constructs6 Population Uniqueness and Natural Selection6.1 Statisticalism and its discontents6.2 Price at what price?7 Conclusion. (shrink)

There is only one physically possible process that builds and operates purposive systems in nature: natural selection. What it does is build and operate systems that look to us purposive, goal directed, teleological. There really are not any purposes in nature and no purposive processes ether. It is just one vast network of linked causal chains. Darwinian natural selection is the only process that could produce the appearance of purpose. That is why natural selection must have built and must continually (...) shape the intentional causes of purposive behavior. Fodor’s argument against Darwinian theory involves a biologist’s modus tollens which is a cognitive scientist’s modus ponens. Assuming his argument is valid, the right conclusion is not that Darwin’s theory is mistaken but that Fodor’s and any other non-Darwinian approaches to the mind are wrong. It shows how getting things wrong in the philosophy of biology leads to mistaken conclusions with the potential to damage the acceptance of a theory with harmful consequences for human well-being. Fodor has shown that the real consequence of rejecting a Darwinian approach to the mind is to reject a Darwinian theory of phylogenetic evolution. This forces us to take seriously a notion that otherwise would not have much of a chance: that when it comes to the nature of mental states, indeterminacy rules. This is an insight that should have the most beneficial impact on freeing cognitive neuroscience from demands on the adequacy of its theories that it could never meet. (shrink)

I provide an explicit formulation of empirical adequacy, the central concept of constructive empiricism, and point out a number of problems. Based on one of the inspirations for empirical adequacy, I generalize the notion of a theory to avoid implausible presumptions about the relation of theoretical concepts and observations, and generalize empirical adequacy with the help of approximation sets to allow for lack of knowledge, approximations, and successive gain of knowledge and precision. As a test case, I provide an application (...) of these generalizations to a simple interference phenomenon. (shrink)

This dissertation consists of three parts. Part I is a defense of an artificial language methodology in philosophy and a historical and systematic defense of the logical empiricists' application of an artificial language methodology to scientific theories. These defenses provide a justification for the presumptions of a host of criteria of empirical significance, which I analyze, compare, and develop in part II. On the basis of this analysis, in part III I use a variety of criteria to evaluate the scientific (...) status of intelligent design, and further discuss confirmation, reduction, and concept formation. (shrink)

In this paper I analyze the difficult question of the truth of mature scientific theories by tackling the problem of the truth of laws. After introducing the main philosophical positions in the field of scientific realism, I discuss and then counter the two main arguments against realism, namely the pessimistic metainduction and the abstract and idealized character of scientific laws. I conclude by defending the view that well-confirmed physical theories are true only relatively to certain values of the variables that (...) appear in the laws. (shrink)

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)

In a recent article, “Wayward Modeling: Population Genetics and Natural Selection,” Bruce Glymour claims that population genetics is burdened by serious predictive and explanatory inadequacies and that the theory itself is to blame. Because Glymour overlooks a variety of formal modeling techniques in population genetics, his arguments do not quite undermine a major scientific theory. However, his arguments are extremely valuable as they provide definitive proof that those who would deploy classical population genetics over natural systems must do so with (...) careful attention to interactions between individual population members and environmental causes. Glymour’s arguments have deep implications for causation in classical population genetics. (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)

Recent work on the semantic view of scientific theories is highly critical of the position. This paper identifies two common criticisms of the view, describes two popular alternatives for responding to them, and argues those responses do not suffice. Subsequently, it argues that retuning to Patrick Suppes’ interpretation of the position provides the conceptual resources for rehabilitating the semantic view.

Mark Colyvan uses applications of mathematics to argue that mathematical entities exist. I claim that his argument is invalid based on the assumption that a certain way of thinking about applications, called `the mapping account,' is correct. My main contention is that successful applications depend only on there being appropriate structural relations between physical situations and the mathematical domain. As a variety of non-realist interpretations of mathematics deliver these structural relations, indispensability arguments are invalid.

Are there genuine mathematical explanations of physical phenomena, and if so, how can mathematical theories, which are typically thought to concern abstract mathematical objects, explain contingent empirical matters? The answer, I argue, is in seeing an important range of mathematical explanations as structural explanations, where structural explanations explain a phenomenon by showing it to have been an inevitable consequence of the structural features instantiated in the physical system under consideration. Such explanations are best cast as deductive arguments which, by virtue (...) of their form, establish that, given the mathematical structure instantiated in the physical system under consideration, the explanandum had to occur. Against the claims of platonists such as Alan Baker and Mark Colyvan, I argue that formulating mathematical explanations as structural explanations in this way shows that we can accept that mathematics can play an indispensable explanatory role in empirical science without committing to the existence of any abstract mathematical objects. (shrink)

In Simulation and Similarity, Michael Weisberg offers a similarity-based account of the model–world relation, which is the relation in virtue of which successful models are successful. Weisberg’s main idea is that models are similar to targets in virtue of sharing features. An important concern about Weisberg’s account is that it remains silent on what it means for models and targets to share features, and consequently on how feature-sharing contributes to models’ epistemic success. I consider three potential ways of concretizing the (...) concept of shared features: as identical, quantitatively sufficiently close, and sufficiently similar features. I argue that each of these concretizations faces significant challenges, leaving unclear how Weisberg’s account substantially contributes to elucidating the relation in virtue of which successful models are successful. Against this background, I outline a pluralistic revision and argue that this revision may not only help Weisberg's account evade several of the problems that I raise, but also offers a novel perspective on the model–world relation more generally. 1Introduction 2Weisberg’s Feature-Sharing Account 3What Is a Shared Feature? 3.1Identity 3.2Sufficient closeness 3.3Sufficient similarity 4Turning Weisberg’s Account ‘Upside Down’ 5Conclusion. (shrink)

Science provides us with representations of atoms, elementary particles, polymers, populations, genetic trees, economies, rational decisions, aeroplanes, earthquakes, forest fires, irrigation systems, and the world’s climate. It's through these representations that we learn about the world. This entry explores various different accounts of scientific representation, with a particular focus on how scientific models represent their target systems. As philosophers of science are increasingly acknowledging the importance, if not the primacy, of scientific models as representational units of science, it's important to (...) stress that how they represent plays a fundamental role in how we are to answer other questions in the philosophy of science. This entry begins by disentangling ‘the’ problem of scientific representation, before critically evaluating the current options available in the literature. (shrink)

In order to develop an account of scientific rationality, two problems need to be addressed: (i) how to make sense of episodes of theory change in science where the lack of a cumulative development is found, and (ii) how to accommodate cases of scientific change where lack of consistency is involved. In this paper, we sketch a model of scientific rationality that accommodates both problems. We first provide a framework within which it is possible to make sense of scientific revolutions, (...) but which still preserves some (partial) relations between old and new theories. The existence of these relations help to explain why the break between different theories is never too radical as to make it impossible for one to interpret the process in perfectly rational terms. We then defend the view that if scientific theories are taken to be quasi-true, and if the underlying logic is paraconsistent, it's perfectly rational for scientists and mathematicians to entertain inconsistent theories without triviality. As a result, as opposed to what is demanded by traditional approaches to rationality, it's not irrational to entertain inconsistent theories. Finally, we conclude the paper by arguing that the view advanced here provides a new way of thinking about the foundations of science. In particular, it extends in important respects both coherentist and foundationalist approaches to knowledge, without the troubles that plague traditional views of scientific rationality. (shrink)

Batterman raises a number of concerns for the inferential conception of the applicability of mathematics advocated by Bueno and Colyvan. Here, we distinguish the various concerns, and indicate how they can be assuaged by paying attention to the nature of the mappings involved and emphasizing the significance of interpretation in this context. We also indicate how this conception can accommodate the examples that Batterman draws upon in his critique. Our conclusion is that ‘asymptotic reasoning’ can be straightforwardly accommodated within the (...) inferential conception. 1 Introduction2 Immersion, Inference and Partial Structures3 Idealization and Surplus Structure4 Renormalization and the Stability of Mathematical Representations5 Explanation and Eliminability6 Requirements for Explanation7 Interpretation and Idealization8 Explanation, Empirical Regularities and the Inferential Conception9 Conclusion. (shrink)

We present a precise form of structural realism, called group structural realism , which identifies ‘structure’ in quantum theory with symmetry groups. However, working out the details of this view actually illuminates a major problem for structural realism; namely, a structure can itself have structure. This article argues that, once a precise characterization of structure is given, the ‘metaphysical hierarchy’ on which group structural realism rests is overly extravagant and ultimately unmotivated.

This paper aims to make progress in understanding the nature of reasoning. Its primary goal is to spell out and defend a novel account of what reasoning might be, in terms of how reasoning contributes to settling (practical and theoretical) inquiries. Prior to spelling out this constructive proposal, however, the paper problematizes a very common picture of reasoning in an attempt to demonstrate the need for an alternative approach. The overarching argument of the paper is comprised of three stages. The (...) first attacks the predominant conception of reasoning for its specious restriction to fully conscious and explicit episodes. The second stage offers a replacement for this faulty conception, according to which a reasoning agent is one who may be represented as if she were undergoing a fully conscious and explicit process. Finally, the last stage proposes one way to fill in the above schema, articulating and defending conditions for representing agents as reasoning fully consciously and explicitly. Each of the above stages is independent of the others: One may accept that reasoning need not be conscious and explicit but reject the schema proposed as a replacement; and again, the schema may be accepted but not the particular proposal for filling it in. (shrink)

This thesis considers the following problem: What methods should the epistemology of science use to gain insight into the structure and behaviour of scientific knowledge and method in actual scientific practice? After arguing that the elucidation of epistemological and methodological phenomena in science requires a method that is rooted in formal methods, I consider two alternative methods for epistemology of science. One approach is the classical approaches of the syntactic and semantic views of theories. I show that typical approaches of (...) this sort are inadequate and inaccurate in their representation of scientific knowledge by showing how they fail to account for and misrepresent important epistemological structure and behaviour in science. The other method for epistemology of science I consider is modeled on the methods used to construct valid models of natural phenomena in applied mathematics. This new epistemological method is itself a modeling method that is developed through the detailed consideration of two main examples of theory application in science: double pendulum systems and the modeling of near-Earth objects to compute probability of future Earth impact. I show that not only does this new method accurately represent actual methods used to apply theories in applied mathematics, it also reveals interesting structural and behavioural patterns in the application process and gives insight into what underlies the stability of methods of application. I therefore conclude that for epistemology of science to develop fully as a scientific discipline it must use methods from applied mathematics, not only methods from pure mathematics and metamathematics as traditional formal epistemology of science has done. (shrink)

Stein once urged us not to confuse the means of representation with that which is being represented. Yet that is precisely what philosophers of science appear to have done at the meta-level when it comes to representing the practice of science. Proponents of the so-called ‘syntactic’ view identify theories as logically closed sets of sentences or propositions and models as idealised interpretations, or ‘theoruncula, as Braithwaite called them. Adherents of the ‘semantic’ approach, on the other hand, are typically characterised as (...) taking them to be families of models that are set-theoretic, according to Suppes and others, or abstract, as Giere has argued. da Costa and French (Science and Partial Truth. OUP, Oxford, 2003) suggested that we should refrain from ontological speculation as to the nature of scientific theories and models and focus on their appropriate representation for various purposes within the philosophy of science. Such an approach allows both linguistic and non-linguistic resources to play their appropriate role (see also French and Saatsi, Philosophy of Science, Proceedings of the 2004 PSA Meeting, 78:548–559, 2006) and can be supported by recent case studies illustrating the heterogeneity of scientific practice. My aim in this paper is to further develop this ‘quietist’ view, and to indicate how it offers a fruitful way forward for the philosophy of science. (shrink)

By exploring the nature of scientific representative practices, I shall define a methodology that relates the use of symmetry to specific practical functions. In order to expound this approach, I shall investigate the role played by the conception of symmetry in representative practices from a philosophical and epistemological perspective. The paper proceeds as follows. In the first part, I introduce the reasons why our conception of representative practices should consider the aims and the objectives towards which they direct their interest. (...) Secondly, by using symmetry as a case study, I try to show that philosophy can find fruitful pathways of interaction with sciences, as it is the case when it deals with the practical implications of the employment of symmetry in modeling. In the third section of the paper I shall refer to other examples that highlight the use of symmetry in scientific representative practices. I shall conclude with some remarks on the implications that this approach involves in epistemology, especially on our conception of objectivity and symmetry. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

In this paper, I provide an account of scientific representation that makes sense of the notion both at the nanoscale and at the quantum level: the partial mappings account. The account offers an extension of a proposal developed by R. I. G. Hughes in terms of denotation, demonstration, and interpretation (DDI). I first argue that the DDI account needs some amendments to accommodate representation of nano and quantum phenomena. I then introduce a generalized framework with the notions of unsharp denotation, (...) unsharp interpretation, and partial mappings. I conclude by arguing that the resulting view not only accommodates nano and quantum representations but also makes sense of representation by imaging in (scanning tunneling) microscopy. (shrink)

Various forms of underdetermination that might threaten the realist stance are examined. That which holds between different 'formulations' of a theory (such as the Hamiltonian and Lagrangian formulations of classical mechanics) is considered in some detail, as is the 'metaphysical' underdetermination invoked to support 'ontic structural realism'. The problematic roles of heuristic fruitfulness and surplus structure in attempts to break these forms of underdetermination are discussed and an approach emphasizing the relevant structural commonalities is defended.

This paper proposes to recover the topic of the philosophy of scientific method from its late nineteenth-century roots. The subject matter of scientific method sprouted from key inferential ingredients identified by Charles Peirce. In this paper, the historical path is traversed from the viewpoint of contemporary Cognitive Structural Realism (CSR). Peirce’s semiotic theory of methods and practices of scientific inquiry prefigured CSR’s reliance on embodied informational structures and experimentation upon forms of relations that model generic scientific domains. Three results are (...) shown to follow from this convocation: (i) a naturalization of Peirce’s interconnected abductive, deductive and inductive stages of the logic of science, here characterized de novo in terms of CSR. (ii) a perspective to scientific modeling that incorporates processes of abstraction and generalization as originated from Peirce’s logic of science, and (iii) diagrammatic reasoning as a pivotal method in analyzing scientific reasoning in experimental practices. (shrink)

In recent years, the use of historical cases in philosophy of science has become a proper topic of reflection. In this article I will contribute to this research by means of a discussion of one very famous example of case-based philosophy of science, namely the debate on the London & London model of superconductivity between Cartwright, Suárez and Shomar on the one hand, and French, Ladyman, Bueno and Da Costa on the other. This debate has been going on for years, (...) without any satisfactory resolution. I will argue here that this is because both sides impose on the historical case a particular philosophical conception of scientific representation that does not do justice to the historical facts. Both sides assume, more specifically, that the case concerns the discovery of a representational connection between a given experimental insight – the Meissner effect – and the diamagnetic meaning of London and London’s new equations of superconductivity. I will show, however, that at the time of the Londons’ publication, neither the experimental insight nor the meaning of the new equations was established: both were open for discussion and they were stabilized only later. On the basis of this historical discussion, I will then propose an alternative approach to the case study: the case should not be seen as a site of confrontation between pre-existing philosophical accounts, but rather as a way to historically elaborate and develop philosophical concepts. I will then show how approaching the historical episode in this way suggests an alternative approach to the philosophical study of representation, according to which it involves the establishment, over time, of a stable connection between constellations of different elements that, through discussion and engagement with alternative views and approaches, come to constitute phenomenon and meaning. (shrink)

Benacerraf has presented two problems for the philosophy of mathematics. These are the problem of identification and the problem of representation. This paper aims to reconstruct the latter problem and to unpack its undermining bearing on the version of Ontic Structural Realism that frames scientific representations in terms of abstract structures. I argue that the dichotomy between mathematical structures and physical ones cannot be used to address the Benacerraf problem but strengthens it. I conclude by arguing that versions of OSR (...) that do not rely on mathematical frameworks for representational purposes need not be vulnerable to Benacerraf’s second problem. (shrink)

In this paper I begin with a recent challenge to the Semantic Approach and identify an underlying assumption, namely that identity conditions for theories should be provided. Drawing on previous work, I suggest that this demand should be resisted and that the Semantic Approach should be seen as a philosophical device that we may use to represent certain features of scientific practice. Focussing on the partial structures variant of that approach, I then consider a further challenge that arises from a (...) concern with the role of idealisations in that practice. I argue that the partial structures approach is capable of meeting this challenge and I conclude with some broader observations about the role of such formal accounts within the philosophy of science. (shrink)

. In this paper, I examine three models of reduction. The first, and the most restrictive, is the model developed by Ernest Nagel as part of the logical empiricist program. The second, articulated by Jerry Fodor, is significantly broader, but it seems unable to make sense of a salient feature of scientific practice. The third, and the most lenient, model is developed within Newton da Costa and Steven French’s partial structures approach. I argue that the third model preserves the benefits (...) of Fodor’s proposal, and it is still able to accommodate relevant aspects of scientific practice. In particular, it offers a conception of reduction without reductionism, and an account of the relation between reduced and reducing theories via unsharp mappings and partial structures—even in the presence of incomplete information. (shrink)

In “The Toolbox of Science” (1995) together with Towfic Shomar we advocated a form of instrumentalism about scientific theories. We separately developed this view further in a number of subsequent works. Steven French, James Ladyman, Otavio Bueno and Newton Da Costa (FLBD) have since written at least eight papers and a book criticising our work. Here we defend ourselves. First we explain what we mean in denying that models derive from theory – and why their failure to do so should (...) be lamented. Second we defend our use of the London model of superconductivity as an example. Third we point out both advantages and weaknesses of FLBD’s techniques in comparison to traditional Anglophone versions of the semantic conception. Fourth we show that FLBD’s version of the semantic conception has not been applied to our case study. We conclude by raising doubts about FLBD’s overall project. (shrink)

Scientific change has two important dimensions: conceptual change and structural change. In this paper, I argue that the existence of conceptual change brings serious difficulties for scientific realism, and the existence of structural change makes structural realism look quite implausible. I then sketch an alternative account of scientific change, in terms of partial structures, that accommodates both conceptual and structural changes. The proposal, however, is not realist, and supports a structuralist version of van Fraassen’s constructive empiricism (structural empiricism).