This thesis is concerned with establishing a bridge between matters of aesthetics and epistemology, by investigating the mechanisms through which artworks allow agents to derive knowledge through the former’s manipulation. It is proposed that, in order to understand the epistemic potential of artworks, we need to approach them as diagrams, in the sense developed by Charles Peirce. The background upon which the arguments are developed are mainly those of American Pragmatism – with a special emphasis on primary literature from Charles (...) Sanders Peirce about semiotics and inquiry, and John Dewey about aesthetics. It is introduced that the manipulation upon artworks can be an example of an inquiry process, due to artworks’ diagrammatic symbol-type-token structure, which embody the logical relations of abduction, deduction and induction. Through Peirce’s definition of inquiry, and Dewey’s definition of an aesthetic experience, it is possible to defend that artworks deliberate create states of doubt and chance as to stimulate and guide inquiry as a way to achieve an aesthetic experience, corroborating to the claim that inquiry processes and aesthetic experience share the same ontological basis: it is in the nature of aesthetic experience to confront agents and contexts with state of chance and doubt, to be further guided through inference into a state of regularity and belief. In order to develop and test the argument, I present the development of Arthur Danto’s influential theory of aesthetics based on Andy Warhol’s Brillo Boxes, by focusing on a review of Danto’s main writings about it. The central point that Danto developed in this theory is that what gives something the status of an artwork are not the immediately perceivable sensorial features of an artifact, but something else. I claim it to be a “diagrammatic structure” that can be potentially manipulated through an inquiry process. I conclude by establishing a possible development of my argument in relation to modelling processes: as diagrams, artworks can be understood as models, opening room for the emergence of new hypothesis and conjectures about the relationship between aesthetics and epistemology. (shrink)

Elaboramos una versión del disposicionalismo experimental que esclarece la relación entre capacidades y leyes fenomenológicas. Tras algunas consideraciones introductorias, presentamos el disposicionalismo experimental en vistas de las nociones de modalidad física y ambiente de estímulo. Trazamos las líneas generales para una epistemología experimentalista de las capacidades y esclarecemos la modalidad física e invariancia de las leyes fenomenológicas. Luego examinamos las generalizaciones físicas y extrapolaciones de las leyes fenomenológicas y exponemos el caso de la ley de Fresnel, que ilustra aspectos de (...) nuestro argumento. Concluimos con algunas consideraciones sobre los límites del disposicionalismo experimental. (shrink)

This volume argues for a new image of science that understands both natural and social phenomena to be the product of mechanisms, casting the work of science as an effort to understand those mechanisms. Glennan offers an account of the nature of mechanisms and of the models used to represent them in physical, life, and social sciences.

A common approach in biosemiotics suggests that semiosis (any activity or process that involves signs) is a natural process embedded in evolution, which entails the production of meaningful processes. As Pattee has argued, a closer look at living systems shows that semiosis is closely related to a very specific and highly functional context of selected constraints. Symbolic control consists in 1) instituting a friction on the novelty, variability and randomness of life processes 2) allowing survival value at all levels of (...) biological organization and 3) enabling self-organization. Then it would be the network of semiotic controls to actually playing a pivotal role in biological organization and evolution. (shrink)

The discovery of high-level causal relations seems a central activity of the special sciences. Those same sciences are less successful in formulating strict laws. If causation must be underwritten by strict laws, we are faced with a puzzle, which might be dubbed the 'no strict laws' problem for high-level causation. Attempts have been made to dissolve this problem by showing that leading theories of causation do not in fact require that causation be underwritten by strict laws. But this conclusion has (...) been too hastily drawn. Philosophers have tended to equate non-strict laws with ceteris paribus laws. I argue that there is another category of non-strict law that has often not been properly distinguished: namely, minutiae rectus laws. If, as it appears, many special science laws are minutiae rectus laws, then this poses a problem for their ability to underwrite causal relations in a way that their typically ceteris paribus nature does not. I argue that the best prospect for resolving the resurgent 'no strict laws' problem is to argue that special science laws are in fact typically probabilistic, rather than being minutiae rectus laws. (shrink)

This paper analyses the cognitive image schemas structuring the ontological commitments of dominant conceptions of ethics and economics to show that the content of economics is implicated in conceptions of ethics, and that these conceptions cannot be separated from questions of research and professional ethics. This analysis of the metaphoric structuring of the ontological commitments of ethics and economics is based on an extension of Kuhn's construct sense of 'paradigm' as concrete analogy; and on techniques of metaphoric analysis developed in (...) cognitive linguistics. Analysis of the iconic and schematic representations of the concrete analogies and idealised cognitive models structuring economic and ethical theories expose both shared and conflicting ontological commitments. Read the Open Peer Discussion on this paper ». (shrink)

Contemporary sociology of scientific knowledge (SSK) is defined by its relativist trend. Its programme often calls for the support of philosophers, such as Duhem, Quine, and Wittgenstein. A critical re-reading of key texts shows that the main principles of relativism are only derivable with difficulty. The thesis of the underdetermination of theory doesn't forbid that Duhem, in many places, validates a correspondence-consistency theory of truth. He never said that social beliefs and interests fill the lack of underdetermination. Quine's idea of (...) a selective revision of hypotheses, as well as the neat incompatibility between holism and conventionalism, openly challenges the principles of relativism. Wittgenstein's work, which is not presented in book-form but rather as a tree, forces us to avoid aphoristic choices that credit any text-excising. This remark allows us to tackle the passages that sociological relativism is based on.Mathematical conventions are not anthropological objects. When Wittgenstein examines the "language-games," he only speaks of the functioning of natural language, not to be confused with scientific formal languages. We then should render the formula "language-game" by "well-defined, explicit and compulsory rules of communication", which is a much less attractive formula for relativism. Consequently, there does not exist a real continuity between the epistemologies of Duhem, Quine and Wittgenstein, and the recent works of the SSK. (shrink)

To date, there is no universal and coherent theory concerning the nature or the function of time. Furthermore, important and unresolved controversies raging within both philosophy and the natural sciences apparently indicate that there is little hope of constructing a single, unified theory. Even so-called "folk" theories of time, embedded within different cultural traditions, show no common elements, and therefore can not provide a pre-theoretical description of time, towards which an explanatory framework could be constructed. This lack of consensus indicates (...) that the concept as it is currently being used is ill defined, and, at the very least, needs to be considerably revised. The conceptual disarray surrounding time has aided and abetted the arguments of certain thinkers, especially Ricoeur, working within the phenomenological tradition who make de principe claims that there can not be a single theory of time. My intention is not to try and to produce a concept of time that was capable of unifying all these different elements. Rather, Ricoeur's arguments and those of others working in the phenomenological tradition dissatisfied me. I believed that their arguments were informed by a myopic, muddled and positively 19th Century understanding of the scientific project. Hence, my aim is to show that Ricoeur's claim will not stand up to scrutiny, and that there are no principled arguments against the possibility of a unified theory of time. We examine the major arguments against unification in general, and also with particular reference to theories of time, such as Husserlian phenomenology, conventionalism, instrumentalism, anti-reductive positions in general, as well as the specific problem of reducing subjective experience to objective description. We demonstrate that none of these objections constitutes a watertight a priori argument against a unified theory of time. Furthermore, we demonstrate that recent developments in the philosophy of science and the philosophy of mind have made such a unified theory a plausible goal. We argue that post-positivist philosophy of science, with its emphasis on research programmes, the co-evolution of theories and super-empirical rational support, opens the way for new types of evidence to be brought to bear on questions about time. Also, recent developments in the brain sciences mean that a neurologically plausible and fully naturalised analysis of our experience of time is being developed. Although much work in this direction has begun, we argue that it is fragmented, partly through the limitations of our current knowledge, but more particularly through an inadequate background of coherent philosophical thought. This has lead both philosophers and scientists to attempt grand metaphysical answers to muddled philosophical questions which threaten the progress which natural science and the philosophy of science have offered in the second half of the twentieth century. (shrink)

Polygenic effects have more than one cause. They testify to the fact that several causal contributors are sometimes simultaneously involved in causation. The importance of polygenic causation was noticed early on by Mill (1893). It has since been shown to be a problem for causal-law approaches to causation and accounts of causation cast in terms of capacities. However, polygenic causation needs to be examined more thoroughly in the emerging literature on causal mechanisms. In this paper I examine whether an influential (...) theory of mechanisms proposed by Peter Machamer, Lindley Darden and Carl Craver can accommodate polygenic effects and other forms of causal interaction. This theory is problematic, I will argue, because it ascribes a central role to activities. In it, activities are needed not only to constitute mechanisms but also to perform the causal role of mechanisms. Any such mechanism-as-activity will be incompatible with causal situations where either no or merely another kind of activity occurs. But, as I will try to illustrate in this paper, both kinds of situation may be frequent. If I am right, the view that Machamer and colleagues suggest leads to an impoverished conception of mechanism. (shrink)

In this paper I investigate the prospects of integrated history and philosophy of science, by examining how philosophical issues concerning experimental practice and scientific realism can enrich the historical investigation of the careers of "hidden entities", entities that are not accessible to unmediated observation. Conversely, I suggest that the history of those entities has important lessons to teach to the philosophy of science. My overall aim is to illustrate the possibility of a fruitful two-way traffic between history and philosophy of (...) science. (shrink)

Examining the role of dispositions (potentials and propensities) in both physics and psychology reveals that they are commonly derivative dispositions, so called because they derive from other dispositions. Furthermore, when they act, they produce further propensities. Together, therefore, they appear to form discrete degrees within a structure of multiple generative levels. It is then constructively hypothesized that minds and physical nature are themselves discrete degrees within some more universal structure. This gives rise to an effective dualism of mind and nature, (...) but one according to which they are still constantly related by causal connections. I suggest a few of the unified principles of operation of this more complicated but universal structure. (shrink)

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

One of the most unsettling problems in the history of philosophy examines how mathematics can be used to adequately represent the world. An influential thesis, stated by Eugene Wigner in his paper entitled "The Unreasonable Effectiveness of Mathematics in the Natural Sciences," claims that "the miracle of the appropriateness of the language of mathematics for the formulation of the laws of physics is a wonderful gift which we neither understand nor deserve." Contrary to this view, this thesis delineates and implements (...) a strategy to show that the applicability of mathematics is very reasonable indeed. I distinguish three forms of the problem of the applicability of mathematics, and focus on one I call the problem of uncanny accuracy: Given that the construction and manipulation of mathematical representations is pervaded by uncertainty, error, approximation, and idealization, how can their apparently uncanny accuracy be explained? I argue that this question has found no satisfactory answer because our rational reconstruction of scientific practice has not involved tools rich enough to capture the logic of mathematical modelling. Thus, I characterize a general schema of mathematical analysis of real systems, focusing on the selection of modelling assumptions, on the construction of model equations, and on the extraction of information, in order to address contextually determinate questions on some behaviour of interest. A concept of selective accuracy is developed to explain the way in which qualitative and quantitative solutions should be utilized to understand systems. The qualitative methods rely on asymptotic methods and on sensitivity analysis, whereas the quantitative methods are best understood using backward error analysis. The basic underpinning of this perspective is readily understandable across scientific fields, and it thereby provides a view of mathematical tractability readily interpretable in the broader context of mathematical modelling. In addition, this perspective is used to discuss the nature of theories, the role of scaling, and the epistemological and semantic aspects of experimentation. In conclusion, we argue for a method of local and global conceptual analysis that goes beyond the reach of the tools standardly used to capture the logic of science; on their basis, the applicability of mathematics finds itself demystified. (shrink)

John Earman and John T. Roberts advocate a challenging and radical claim regarding the semantics of laws in the special sciences: the statistical account. According to this account, a typical special science law “asserts a certain precisely defined statistical relation among well-defined variables” and this statistical relation does not require being hedged by ceteris paribus conditions. In this paper, we raise two objections against the attempt to cash out the content of special science generalizations in statistical terms.

If dispositions are conceived as properties of systems that refer to possible causal relations, dispositions can be used in singular causal explanations. By means of these dispositional explanations, we can explain behavior B of a system x by (i) referring to a situation of type S that triggered B, given that x has a disposition D to do B in S, or (ii) by referring to a disposition D of x to do B in S, given that x is in (...) a situation of type S. Dispositional explanations are adequate and indispensable explanations: they can explain behavior B without explicitly referring to the underlying causal basis in x that constitutes a disposition to do B. Radical Behaviorist explanations are a sort of dispositional explanations, but the dispositional model is not restricted to these explanations. The dispositional model is compatible with, or can be applied to, several research programs. (shrink)

The paper investigates what is meant by "good science" and "bad science" and how these differ as between the natural (physical and biological) sciences on the one hand and social sciences on the other. We conclude on the basis of historical evidence that the natural science are much more heavily constrained by evidence and observation than by theory while the social sciences are constrained by prior theory and hardly at all by direct evidence. Current examples of the latter proposition are (...) taken from recent issues of leading social science journals. We argue that agent based social simulations can be used as a tool to constrain the development of a new social science by direct (what economists dismiss as anecdotal) evidence and that to do so would make social science relevant to the understanding and influencing of social processes. We argue that such a development is both possible and desirable. We do not argue that it is likely. (shrink)

Our point of departure is Russell’s (1913) argument for the ‘complete extrusion’ of the word ‘cause’ from the philosophical vocabulary. We argue that at least three different types of philosophical project concerning ‘cause’ should be carefully distinguished, and that failures to distinguish them lie at the root of some apparently recalcitrant problems. We call them the ‘cognitive’, the ‘scientific’ and the ‘metaphysical’.

The vagueness or imprecision of ‘the normal’ allows it to be exploited for various purposes and political ends. It is conspicuous in both medicine and athletics; I am going to try to say something about the normal in each of these areas. In medicine the idea of the normal is often deployed in understanding what constitutes disease and hence, as some see it, in determining the role of physicians, in determining what is or ought to be covered by insurance, and (...) in underwriting certain views on social justice. In athletics the use of performance enhancing substances raises different sorts of questions about the normal, especially when it comes to deciding what constitutes an enhancement and which enhancements, if any, are acceptable. (shrink)

This paper argues that there is no conflict between quantum theory and relativity, and that quantum theory itself helps us explain puzzling “non-local” correlations in a way that contradicts neither Bell’s intuitive locality principle nor his local causality condition. The argument depends on understanding quantum theory along pragmatist lines I have outlined elsewhere, and on a more general view of how that theory helps us explain. The key counterfactuals that hold in such cases manifest epistemic rather than causal connections between (...) distant events. Quantum theory exploits the possibility of private informational links between an agent and events he neither observes nor brings about, in ways that are strikingly independent of the spatiotemporal relations between them. This possibility has interesting implications for theories of chance in a relativistic world. (shrink)

In this book Martin Bunzl considers the prospects for a general and comprehensive account of explanation, given the variety of interests that prompt explanations in science. Bunzl argues that any successful account of explanation must deal with two very different contexts - one static and one dynamic. Traditionally, theories of explanation have been built for the former of these two contexts. That is to say, they are designed to show how it is that a 'finished' body of scientific knowledge can (...) be put to explanatory use. But finished sciences are few and far between. Real 'explanation' also occurs in a dynamical context in which questions are asked and answers are given as theories are in the process of being constructed. Here, Bunzl argues that attending to explanation produced under these dynamic circumstances undermines prominent features of the theory of explanation produced in the traditional static context. (shrink)

The aim of this paper is to re-emphasise that the purpose of formal systems is to provide something to map into and to stem the tide of unjustified formal systems. I start by arguing that expressiveness alone is not a sufficient justification for a new formal system but that it must be justified on pragmatic grounds. I then deal with a possible objection as might be raised by a pure mathematician and after that to the objection that theory can be (...) later used by more specific models. I go on to compare two different methods of developing new formal systems: by a priori principles and intuitions; and by post hoc generalisation from data and examples. I briefly describe the phenomena of “social embedding” and use it to explain the social processes that underpin “normal” and “revolutionary” science. This suggests social grounds for the popularity of normal science. I characterise the “foundational” and “empirical” approaches to the use of formal systems and situate these with respect to “normal” and “revolutionary” modes of science. I suggest that successful sciences (in the sense of developing relevant mappings to formal systems) bare either more tolerant of revolutionary ideas or this tolerance is part of the reason they are successful. I finish by enumerating a number of ‘tell-tale’ signs that a paper is presenting an unjustified formal system. (shrink)

Traditional accounts of explanation fail to illuminate the explanatory relevance of “models that are descriptively false” in the sense that the regularities they entail fail to obtain. In this paper, I propose an account of explanation, which I call ‘explanation by concretization’, that serves to explicate the explanatory relevance of such models. Starting from a highly abstract and idealized model, causal explanations of the absence of regularities are sought by adding complexity to the model or by concretizing it. Whether this (...) process is successful depends on whether the abstractions and idealizations in the basic model succeed in isolating a mechanism, i.e. in representing how it operates when interfering factors are absent. This account is developed in the context of economics and contrasted to those of Daniel Hausman and Nancy Cartwright. I go on to provide an account of how unrealistic models can be used for providing understanding of the way mechanisms work. (shrink)

Selection explanations explain some non-accidental generalizations in virtue of a selection process. Such explanations are not particulaizable - they do not transfer as explanations of the instances of such generalizations. This is unlike many explanations in the physical sciences, where the explanation of the general fact also provides an explanation of its instances (i.e. standard D-N explanations). Are selection explanations (e.g. in biology) therefore a different kind of explanation? I argue that to understand this issue, we need to see that (...) a standard D-N explanation of some non-accidental generalization (al Fs are Gs) may also ipso facto explain its contrapositive (all non-Gs are non-Fs), but the explanation is particularizable with respect to the former but not to the latter. This can be seen by noting that the Raven Paradox counterexample to the H-D model of confirmation also generates a counterexample to the D-N model of explanation (all ravens are black does not explain why the non-black shoe is a non-raven). In such cases it is natural to take the generalization with the positive predicates to have a particularizable explanation. However, this need not be the case, and in selection explanations it is the generalization with the positive predicates whose explanation is no particularizable. Thus there is no need to suppose that selection explanations are fundamentally different. (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)

The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. There are two different approaches to deal with the justification of a model: an axiomatic and an empirical approach. The axiomatic approach verifies whether a given relational structure satisfies certain axioms to secure homomorphic mapping. The empirical approach conceives models to function as measuring instruments by transferring observations of a phenomenon under investigation into quantitative facts about that phenomenon. These facts (...) are evaluated by their accuracy and precision. Precision is generally achieved by least squares methods and accuracy by calibration. For calibration standards are needed. Then two polar strategies can be distinguished: white-box modeling and black-box modeling. The first strategy of modeling aims at estimating the invariant equations of the phenomenon, thereby fulfilling Hertz’s correctness requirement. The latter strategy of modeling is to use known stable facts about the phenomenon to adjust the model parameters, thereby fulfilling Hertz’s appropriateness requirement. For this latter strategy, the requirement of models as homomorphic mappings has been dropped. Where one will find the axiomatic approach more often used for measurement in the laboratory, the empirical approach is more appropriate for measurement outside the laboratory. The reason for this is that for measurement of phenomena outside the laboratory, one also needs to take account of the environment to achieve accurate results. Environments are generally too relation-rich for an axiomatic approach, which are only applicable for relation-poor systems. The white-box modeling strategy, reflecting the complexity of the environment due to its correctness requirement, will, however, lead to immensely large models. To avoid this problem, modular design is an appropriate strategy to reduce this complexity. Modular design is a grey-box modeling strategy. Grey-box models are assemblies of modules; these are black boxes with standard interface. It should be noted that the structure of the assemblage need not be homomorphic to the relations describing the interaction between phenomenon and environment. These three modeling strategies map out the possible designs for computer simulations as measuring instruments. Whether a simulation is based on a white-box, grey-box or black-box model is only determined by the relationship between the phenomenon and its environment and not by e.g. its materiality or physicality. (shrink)

The thesis is a philosophical analysis of the consumption based capital asset pricing model, investigating in particular its epistemological and methodological foundations. Financial markets are integral parts of advanced and developing economies. They matter because they channel unspent household income into banks’ savings accounts and assets such as bonds and stocks. Financial economists have traditionally taken interest in the pricing mechanism that underlies this capital allocation. The consumption based capital asset pricing model is a prominent effort to describe, explain and (...) predict such prices. It tells a story of investors’ trade-off between consumption now and later and which portfolio of assets to hold. The CCAPM based narrative intuitively makes sense, and the chosen methodology involving theoretical assumption, mathematical models and empirical tests follows the professions’ standards of good scientific practise. But does CCAPM’s research programme provide knowledge for use? My thesis seeks to answer this question in a novel way. Instead of embarking on yet another asset pricing research project, I let Philosophy of Science inform my analysis. Following a “primer” introducing essential CCAPM topics and notations, I discuss, in turn, its theoretical foundation, mathematical model, and empirical test results from a philosophy of science perspective. I find that a few fundamental principles and several auxiliary assumptions combine to develop a simplified, partial and idealized theory of investors, financial markets and assets. The model reflects and represents this theory but also makes narrow claims that are distances away from the real situations they target. Unsurprisingly, ideal model assertions fail standard statistical tests of significance. I conclude that mathematical deductive modelling rooted in orthodox, a priori based fundamental principles create ideal and fictional settings that limit their scope and portability. The development of even more granular models within this orthodox paradigm that searches for “event regularities” will not render the desired knowledge for use. The real situations are possibly too complex to be captured in simplified assumptions, ideal theories and mathematical structures. Novel methodological and ontological approaches to asset pricing are in demand. Hence, claims about tendencies in the real data might replace the current focus on point-forecasts. (shrink)

This book is a sustained defense of the compatibility of the presence of idealizations in the sciences and scientific realism. So, the book is essentially a detailed response to the infamous arguments raised by Nancy Cartwright to the effect that idealization and scientific realism are incompatible.

It has become increasingly clear that natural phenomena cannot be formally deduced from laws but that almost every phenomenon has its own particular way of being linked to higher-level generalizations, usually via approximations, normalizations and corrections. This article deals with the following problem: if there are no general principles to link laws to phenomena, and if each phenomenon has its own way of being explained, how can we -- or how can a theory -- explain any new phenomenon? I will (...) argue that while particular explanations only apply to the specific phenomena they describe, parts of such explanations can be productively reused in explaining new phenomena. This leads to a view on theory, which I call maximalism, according to which new phenomena are understood in terms of previous phenomena. On the maximalist view, a theory is not a system of axioms or a class of models, but a dynamically updated corpus of explanations. New phenomena are explained by combining fragments of explanations of previous phenomena. I will give an instantiation of this view, based on a corpus of phenomena from classical and fluid mechanics, and show that the maximalist approach is not only used but also needed in scientific practice. (shrink)

The current consensus view of causation in physics, as commonly held by scientists and philosophers, has several serious problems. It fails to provide an epistemology for the causal knowledge that it claims physics to possess; it is inapplicable in a prominent area of physics (classical thermodynamics); and it is difficult to reconcile with our everyday use of causal concepts and claims. In this dissertation, I use historical examples and philosophical arguments to show that the interventionist account of causation constitutes a (...) promising alternative for a “physically respectable” account of causation. The interventionist account explicates important parts of the experimental practice of physics and important aspects of the ways in which physical theory is used and applied. Moreover, the interventionist account succeeds where the consensus view of causation in physics fails. I argue that the interventionist account provides an epistemology of causal knowledge in physics that is rooted in experiment. On the interventionist view, there is a close link between experiment and the testing of causal claims. I give several examples of experiments from the early history of thermodynamics that scientists used in interventionist-type arguments. I also argue that interventionist claims made in the context of a physical theory can be epistemically justified by reference to the experimental interventions and observations that serve as evidence for the theory. I then show that the interventionist account of causation is well-suited to the patterns of reasoning that are intrinsic to thermodynamic theory. I argue that interventionist reasoning constitutes the structural foundation of thermodynamic theory, and that thermodynamic theory can provide clear answers to meaningful questions about whether or not a certain variable is a cause of another in a given context. Finally, I argue that the interventionist account offers the prospect of a unification of “physically respectable” causation and our everyday notion of causation. I conclude the dissertation by sketching an anti-foundationalist unification of causation, according to which causal reasoning occurs in the same manner in physics as it does in other branches of life and scientific research. (shrink)

The context of an operational description is given by the distinction between what we consider as relevant and what as irrelevant for a particular experiment or observation. A rigorous description of a context in terms of a mathematically formulated context-independent fundamental theory is possible by the restriction of the domain of the basic theory and the introduction of a new coarser topology. Such a new topology is never given by first principles, but depends in a crucial way on the abstractions (...) made by the cognitive apparatus or the pattern recognition devices used by the experimentalist. A consistent mathematical formulation of a higher-level theory requires the closure of the restriction of the basic theory in the new contextual topology. The validity domain of the so constructed higher-level theory intersects nontrivially with the validity domain of the basic theory: neither domain is contained in the other. Therefore, higher-level theories cannot be totally ordered and theory reduction is not transitive. The emergence of qualitatively new properties is a necessary consequence of such a formulation of theory reduction (which does not correspond to the traditional one). Emergent properties are not manifest on the level of the basic theory, but they can be derived rigorously by imposing new, contextually selected topologies upon context-independent first principles. Most intertheoretical relations are mathematically describable as singular asymptotic expansions which do not converge in the topology of the primary theory, or by choosing one of the infinitely many possible, physically inequivalent representations of the primary theory (Gelfand–Naimark–Segal-construction of algebraic quantum mechanics). As examples we discuss the emergence of shadows, inductors, capacitors and resistors from Maxwell’s electrodynamics, the emergence of order parameters in statistical mechanics, the emergence of mass as a classical observable in Galilei-relativistic theories, the emergence of the shape of molecules in quantum mechanics, the emergence of temperature and other classical observables in algebraic quantum mechanics. (shrink)

Part of the scientific enterprise is to measure the material world and to explain its dynamics by means of models. However, not only is measurability of the world limited, analyzability of models is so, too. Most often, computer simulations offer a way out of this epistemic bottleneck. They instantiate the model and may help to analyze it. In relation to the material world a simulation may be regarded as a kind of a “non-material scale model”. Like any other scale model, (...) it does not per se give any scientific explanation but is first in itself an object of scientific enquiry, a world. Since this world is numerical, it is a priori measurable. Its role in scientific explanation will be discussed. (shrink)

The nature and status of psychological laws are a long-standing controversy. I will argue that part of the controversy stems from the distinctive nature of an important subset of those laws, which I’ll call “supple laws.” An emergent-model strategy taken by the new interdisciplinary field of artificial life provides a strikingly successful understanding of analogously supple laws in biology. So, after reviewing the failures of the two evident strategies for understanding supple psychological laws, I’ll turn for inspiration to emergent-models explanations (...) of supple laws in biology. I’ll conclude by inferring what an emergent model of supple laws in psychology should be like. (shrink)

The talk given on 10 January 2017 during the workshop "The Arbitrariness of the Sign" at "Le cours de linguistique générale 1916-2016" conference in Geneva.