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  1. Making things happen: a theory of causal explanation.James F. Woodward - 2003 - New York: Oxford University Press.
    Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.
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  • (1 other version)Scientific Explanation and the Causal Structure of the World.Wesley C. Salmon - 1984 - Princeton University Press.
    The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...)
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  • Explaining Behavior: Reasons in a World of Causes.Fred I. Dretske - 1988 - MIT Press.
    In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.
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  • Radical Embodied Cognitive Science.Anthony Chemero - 2009 - Bradford.
    While philosophers of mind have been arguing over the status of mental representations in cognitive science, cognitive scientists have been quietly engaged in studying perception, action, and cognition without explaining them in terms of mental representation. In this book, Anthony Chemero describes this nonrepresentational approach, puts it in historical and conceptual context, and applies it to traditional problems in the philosophy of mind. Radical embodied cognitive science is a direct descendant of the American naturalist psychology of William James and John (...)
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  • Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research.William Bechtel & Robert C. Richardson - 2010 - Princeton.
    An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...)
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  • Simulation and Similarity: Using Models to Understand the World.Michael Weisberg - 2013 - New York, US: Oxford University Press.
    one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...
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  • Depth: An Account of Scientific Explanation.Michael Strevens - 2008 - Cambridge: Harvard University Press.
    Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.
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  • Functional analysis.Robert E. Cummins - 1975 - Journal of Philosophy 72 (November):741-64.
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  • Psychological Explanation: An Introduction To The Philosophy Of Psychology.Jerry A. Fodor - 1968 - Ny: Random House.
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  • Explanatory unification and the causal structure of the world.Philip Kitcher - 1962 - In Philip Kitcher & Wesley C. Salmon (eds.), Scientific Explanation. Univ of Minnesota Pr. pp. 410-505.
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  • (1 other version)Knowledge and the Flow of Information.Fred I. Dretske - 1981 - Revue Philosophique de la France Et de l'Etranger 175 (1):69-70.
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  • Causal explanation.David Lewis - 1986 - In Philosophical Papers, Volume II. New York, US: Oxford University Press. pp. 214-240.
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  • (1 other version)Four Decades of Scientific Explanation.Wesley C. Salmon & Anne Fagot-Largeault - 1989 - History and Philosophy of the Life Sciences 16 (2):355.
    As Aristotle stated, scientific explanation is based on deductive argument--yet, Wesley C. Salmon points out, not all deductive arguments are qualified explanations. The validity of the explanation must itself be examined. _Four Decades of Scientific Explanation_ provides a comprehensive account of the developments in scientific explanation that transpired in the last four decades of the twentieth century. It continues to stand as the most comprehensive treatment of the writings on the subject during these years. Building on the historic 1948 essay (...)
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  • Reasons Why.Bradford Skow - 2016 - Oxford, England and New York, NY, USA: Oxford University Press UK.
    This book first argues that what philosophers are really after, or at least should be after, when they seek a theory of explanation, is a theory of answers to why-questions. The book's main thesis, then, is a theory of reasons why. Every reason why some event happened is either a cause, or a ground, of that event. Challenging this thesis are many examples philosophers have thought they have found of "non-causal explanations." Reasons Why uses two ideas to show that these (...)
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  • Integrating psychology and neuroscience: functional analyses as mechanism sketches.Gualtiero Piccinini & Carl Craver - 2011 - Synthese 183 (3):283-311.
    We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...)
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  • Minimal Model Explanations.Robert W. Batterman & Collin C. Rice - 2014 - Philosophy of Science 81 (3):349-376.
    This article discusses minimal model explanations, which we argue are distinct from various causal, mechanical, difference-making, and so on, strategies prominent in the philosophical literature. We contend that what accounts for the explanatory power of these models is not that they have certain features in common with real systems. Rather, the models are explanatory because of a story about why a class of systems will all display the same large-scale behavior because the details that distinguish them are irrelevant. This story (...)
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  • Are More Details Better? On the Norms of Completeness for Mechanistic Explanations.Carl F. Craver & David M. Kaplan - 2020 - British Journal for the Philosophy of Science 71 (1):287-319.
    Completeness is an important but misunderstood norm of explanation. It has recently been argued that mechanistic accounts of scientific explanation are committed to the thesis that models are complete only if they describe everything about a mechanism and, as a corollary, that incomplete models are always improved by adding more details. If so, mechanistic accounts are at odds with the obvious and important role of abstraction in scientific modelling. We respond to this characterization of the mechanist’s views about abstraction and (...)
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  • The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective.David Michael Kaplan & Carl F. Craver - 2011 - Philosophy of Science 78 (4):601-627.
    We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are (...)
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  • Program explanation: A general perspective.Frank Jackson & Philip Pettit - 1990 - Analysis 50 (2):107-17.
    Some properties are causally relevant for a certain effect, others are not. In this paper we describe a problem for our understanding of this notion and then offer a solution in terms of the notion of a program explanation.
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  • The Ontic Account of Scientific Explanation.Carl F. Craver - 2014 - In Marie I. Kaiser, Oliver R. Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special science: The case of biology and history. Dordrecht: Springer. pp. 27-52.
    According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...)
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  • An inferential conception of scientific representation.Mauricio Suárez - 2004 - Philosophy of Science 71 (5):767-779.
    This paper defends an inferential conception of scientific representation. It approaches the notion of representation in a deflationary spirit, and minimally characterizes the concept as it appears in science by means of two necessary conditions: its essential directionality and its capacity to allow surrogate reasoning and inference. The conception is defended by showing that it successfully meets the objections that make its competitors, such as isomorphism and similarity, untenable. In addition the inferential conception captures the objectivity of the cognitive representations (...)
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  • (3 other versions)Scientific Explanation.P. Kitcher & W. C. Salmon - 1992 - British Journal for the Philosophy of Science 43 (1):85-98.
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  • Scientific representation, interpretation, and surrogative reasoning.Gabriele Contessa - 2007 - Philosophy of Science 74 (1):48-68.
    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 (...)
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  • Moving Beyond Causes: Optimality Models and Scientific Explanation.Collin Rice - 2013 - Noûs 49 (3):589-615.
    A prominent approach to scientific explanation and modeling claims that for a model to provide an explanation it must accurately represent at least some of the actual causes in the event's causal history. In this paper, I argue that many optimality explanations present a serious challenge to this causal approach. I contend that many optimality models provide highly idealized equilibrium explanations that do not accurately represent the causes of their target system. Furthermore, in many contexts, it is in virtue of (...)
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  • Probability, explanation, and information.Peter Railton - 1981 - Synthese 48 (2):233 - 256.
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  • Models and mechanisms in psychological explanation.Daniel A. Weiskopf - 2011 - Synthese 183 (3):313-338.
    Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of techniques for abstracting (...)
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  • In Defense of Explanatory Ecumenism.Frank Jackson - 1992 - Economics and Philosophy 8 (1):1-21.
    Many of the things that we try to explain, in both our common sense and our scientific engagement with the world, are capable of being explained more or less finely: that is, with greater or lesser attention to the detail of the producing mechanism. A natural assumption, pervasive if not always explicit, is that other things being equal, the more finegrained an explanation, the better. Thus, Jon Elster, who also thinks there are instrumental reasons for wanting a more fine-grained explanation, (...)
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  • Social knowing: The social sense of 'scientific knowledge'.Alexander Bird - 2010 - Philosophical Perspectives 24 (1):23-56.
    There is a social or collective sense of ‘knowledge’, as used, for example, in the phrase ‘the growth of scientific knowledge’. In this paper I show that social knowledge does not supervene on facts about what individuals know, nor even what they believe or intend, or any combination of these or other mental states. Instead I develop the idea that social knowing is an analogue to individual knowing, where the analogy focuses on the functional role of social and individual knowing.
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  • After the Philosophy of Mind: Replacing Scholasticism with Science.Tony Chemero & Michael Silberstein - 2008 - Philosophy of Science 75 (1):1-27.
    We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...)
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  • Minimal models and canonical neural computations: the distinctness of computational explanation in neuroscience.M. Chirimuuta - 2014 - Synthese 191 (2):127-153.
    In a recent paper, Kaplan (Synthese 183:339–373, 2011) takes up the task of extending Craver’s (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model’s explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in (...)
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  • Three kinds of new mechanism.Arnon Levy - 2013 - Biology and Philosophy 28 (1):99-114.
    I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.
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  • Are There Non-Causal Explanations (of Particular Events)?Bradford Skow - 2014 - British Journal for the Philosophy of Science 65 (3):445-467.
    Philosophers have proposed many alleged examples of non-causal explana- tions of particular events. I discuss several well-known examples and argue that they fail to be non-causal.
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  • Minimal Models and the Generalized Ontic Conception of Scientific Explanation.Mark Povich - 2018 - British Journal for the Philosophy of Science 69 (1):117-137.
    Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) they propose (...)
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  • Are There Non-Causal Explanations (of Particular Events)?Brdford Skow - 2013 - British Journal for the Philosophy of Science (3):axs047.
    Philosophers have proposed many alleged examples of non-causal explanations of particular events. I discuss several well-known examples and argue that they fail to be non-causal. 1 Questions2 Preliminaries3 Explanations That Cite Causally Inert Entities4 Explanations That Merely Cite Laws I5 Stellar Collapse6 Explanations That Merely Cite Laws II7 A Final Example8 Conclusion.
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  • Equilibrium explanation.Elliott Sober - 1983 - Philosophical Studies 43 (2):201 - 210.
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  • Program explanation: a general perspective.Frank Jackson & Alonso Church - 1990 - Analysis 50 (2):107.
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  • The Nature of Dynamical Explanation.Carlos Zednik - 2011 - Philosophy of Science 78 (2):238-263.
    The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. Therefore, contemporary dynamicist (...)
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  • Mechanistic explanation without the ontic conception.Cory Wright - 2012 - European Journal of Philosophy of Science 2 (3):375-394.
    The ontic conception of scientific explanation has been constructed and motivated on the basis of a putative lexical ambiguity in the term explanation. I raise a puzzle for this ambiguity claim, and then give a deflationary solution under which all ontically-rendered talk of explanation is merely elliptical; what it is elliptical for is a view of scientific explanation that altogether avoids the ontic conception. This result has revisionary consequences for New Mechanists and other philosophers of science, many of whom have (...)
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  • A Field Guide to Mechanisms: Part I.Holly Andersen - 2014 - Philosophy Compass 9 (4):274-283.
    In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning distinct senses. The ‘new mechanisms’ (...)
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  • Philosophy for the Rest of Cognitive Science.Nigel Stepp, Anthony Chemero & Michael T. Turvey - 2011 - Topics in Cognitive Science 3 (2):425-437.
    Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel’s (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). We then propose a philosophy of science appropriate to nonrepresentational, dynamical (...)
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  • Socially extended knowledge.Jennifer Lackey - 2014 - Philosophical Issues 24 (1):282-298.
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  • Mechanistic Explanation: Integrating the Ontic and Epistemic.Phyllis Illari - 2013 - Erkenntnis 78 (2):237-255.
    Craver claims that mechanistic explanation is ontic, while Bechtel claims that it is epistemic. While this distinction between ontic and epistemic explanation originates with Salmon, the ideas have changed in the modern debate on mechanistic explanation, where the frame of the debate is changing. I will explore what Bechtel and Craver’s claims mean, and argue that good mechanistic explanations must satisfy both ontic and epistemic normative constraints on what is a good explanation. I will argue for ontic constraints by drawing (...)
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  • Information as a Probabilistic Difference Maker.Andrea Scarantino - 2015 - Australasian Journal of Philosophy 93 (3):419-443.
    By virtue of what do alarm calls and facial expressions carry natural information? The answer I defend in this paper is that they carry natural information by virtue of changing the probabilities of various states of affairs, relative to background data. The Probabilistic Difference Maker Theory of natural information that I introduce here is inspired by Dretske's [1981] seminal analysis of natural information, but parts ways with it by eschewing the requirements that information transmission must be nomically underwritten, mind-independent, and (...)
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  • A Field Guide to Mechanisms: Part II.Holly Andersen - 2014 - Philosophy Compass 9 (4):284-293.
    In this field guide, I distinguish five separate senses with which the term ‘mechanism’ is used in contemporary philosophy of science. Many of these senses have overlapping areas of application but involve distinct philosophical claims and characterize the target mechanisms in relevantly different ways. This field guide will clarify the key features of each sense and introduce some main debates, distinguishing those that transpire within a given sense from those that are best understood as concerning two distinct senses. The ‘new (...)
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  • Materialism.Jerry A. Fodor - 1968 - In Psychological Explanation: An Introduction To The Philosophy Of Psychology. Ny: Random House.
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  • The Functional Unity of Special Science Kinds.Daniel A. Weiskopf - 2011 - British Journal for the Philosophy of Science 62 (2):233-258.
    The view that special science properties are multiply realizable has been attacked in recent years by Shapiro, Bechtel and Mundale, Polger, and others. Focusing on psychological and neuroscientific properties, I argue that these attacks are unsuccessful. By drawing on interspecies physiological comparisons I show that diverse physical mechanisms can converge on common functional properties at multiple levels. This is illustrated with examples from the psychophysics and neuroscience of early vision. This convergence is compatible with the existence of general constraints on (...)
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  • One mechanism, many models: a distributed theory of mechanistic explanation.Eric Hochstein - 2016 - Synthese 193 (5):1387-1407.
    There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that individual models (...)
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  • Mechanistic Explanation in Psychology.Mark Povich - forthcoming - In Hank Stam & Huib Looren De Jong (eds.), The SAGE Handbook of Theoretical Psychology. (Eds.) Hank Stam and Huib Looren de Jong. Sage.
    Philosophers of psychology debate, among other things, which psychological models, if any, are (or provide) mechanistic explanations. This should seem a little strange given that there is rough consensus on the following two claims: 1) a mechanism is an organized collection of entities and activities that produces, underlies, or maintains a phenomenon, and 2) a mechanistic explanation describes, represents, or provides information about the mechanism producing, underlying, or maintaining the phenomenon to be explained (i.e. the explanandum phenomenon) (Bechtel and Abrahamsen (...)
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  • Heuristics, Descriptions, and the Scope of Mechanistic Explanation.Carlos Zednik - 2015 - In Pierre-Alain Braillard & Christophe Malaterre (eds.), Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Dordrecht: Springer. pp. 295-318.
    The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...)
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  • The ontic conception of scientific explanation.Cory Wright - 2015 - Studies in History and Philosophy of Science Part A 54:20-30.
    Wesley Salmon’s version of the ontic conception of explanation is a main historical root of contemporary work on mechanistic explanation. This paper examines and critiques the philosophical merits of Salmon’s version, and argues that his conception’s most fundamental construct is either fundamentally obscure, or else reduces to a non-ontic conception of explanation. Either way, the ontic conception is a misconception.
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