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  1. Holly Andersen (2012). The Case for Regularity in Mechanistic Causal Explanation. Synthese 189 (3):415-432.
    How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...)
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  2. Holly Andersen (2011). Mechanisms, Laws, and Regularities. Philosophy of Science 78 (2):325-331.
    Leuridan (2010) argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and advocates Mitchell’s (1997) pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong between mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature (...)
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  3. Daniela Bailer-Jones, Monika Dullstein & Sabina Pauen (eds.) (2007). Kausales Denken: Philosophische und Psychologische Perspektiven. Mentis.
    Kausales Denken spielt sowohl im Alltag wie auch im wissenschaftlichen Forschungsprozess eine zentrale Rolle. Es erlaubt uns, Phänomene vorherzusagen, zu kontrollieren und zu verstehen. Kausales Denken geht über die Angabe der Ursachen eines Phänomens hinaus: Wollen wir verstehen, warum ein Fahrrad fährt, so versuchen wir, Schritt für Schritt nachzuvollziehen, wie die einzelnen Bestandteile des Fahrrads zusammenwirken, um miteinander die Bewegung zu produzieren. Wir sind an dem Mechanismus interessiert, durch den das Phänomen zustande kommt. Dieses Vorgehen wird in der Wissenschaftsphilosophie wie (...)
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  4. Marina Paola Banchetti-Robino (2011). Ontological Tensions in Sixteenth and Seventeenth Century Chemistry: Between Mechanism and Vitalism. Foundations of Chemistry 13 (3):173-186.
    The sixteenth and seventeenth centuries marks a period of transition between the vitalistic ontology that had dominated Renaissance natural philosophy and the Early Modern mechanistic paradigm endorsed by, among others, the Cartesians and Newtonians. This paper will focus on how the tensions between vitalism and mechanism played themselves out in the context of sixteenth and seventeenth century chemistry and chemical philosophy, particularly in the works of Paracelsus, Jan Baptista Van Helmont, Robert Fludd, and Robert Boyle. Rather than argue that these (...)
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  5. Ingo Brigandt (2015). Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation. In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer. 135–173.
    Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...)
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  6. Ingo Brigandt (2013). Systems Biology and the Integration of Mechanistic Explanation and Mathematical Explanation. Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
    The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation (as the analysis of a whole in terms of its structural parts and their qualitative interactions) have (...)
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  7. Noam Chomsky (2009). The Mysteries of Nature: How Deeply Hidden? Journal of Philosophy 106 (4):167-200.
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  8. Mark B. Couch (2011). Mechanisms and Constitutive Relevance. Synthese 183 (3):375-388.
    This paper will examine the nature of mechanisms and the distinction between the relevant and irrelevant parts involved in a mechanism’s operation. I first consider Craver’s account of this distinction in his book on the nature of mechanisms, and explain some problems. I then offer a novel account of the distinction that appeals to some resources from Mackie’s theory of causation. I end by explaining how this account enables us to better understand what mechanisms are and their various features.
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  9. Carl F. Craver (2006). When Mechanistic Models Explain. Synthese 153 (3):355-376.
    Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...)
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  10. Monika Dullstein (2010). Verursachung und kausale Relevanz. Eine Analyse singulärer Kausalaussagen. mentis.
    Die philosophische Kausaldebatte hat in den vergangenen vier Jahrzehnten eine neue Blüte erlebt. Kontrafaktische, interventionistische, mechanistische und transfertheoretische Ansätze haben sich neben den bislang dominierenden Regularitätstheorien etabliert. Vertreter aller dieser Ansätze sehen sich jedoch mit Gegenbeispielen konfrontiert, keine Theorie scheint allen unseren intuitiven Kausalurteilen gerecht werden zu können. Dieses Buch führt anhand ausgewählter Beispiele in die aktuelle Debatte ein und liefert eine Erklärung für die derzeitige Patt-Situation. Der Grund dafür, dass sich zu jedem Ansatz offenbar mühelos Gegenbeispiele finden lassen, liegt, (...)
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  11. Carla Fehr, Sex and Explanatory Pluralism: Is It a Case of Causal Mechanism Versus Unifying Theories of Explanation?
    There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.
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  12. Laura Felline (forthcoming). Mechanisms Meet Structural Explanation. Synthese.
    This paper investigates the relationship between Structural Explanation and the New Mechanistic account of explanation. The aim of this paper is twofold: firstly, to argue that some phenomena in the domain of fundamental physics, although mechanically brute, are structurally explained; and secondly, by elaborating on the contrast between SE and ME, to better clarify some features of SE. Finally, this paper will argue that, notwithstanding their apparently antithetical character, SE and ME can be reconciled within a unified account of general (...)
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  13. L. R. Franklin-Hall, The Emperor's New Mechanisms.
    This paper argues that the increasingly dominant new mechanistic approach to scientific explanation, as developed to date, does not shed new light on explanatory practice. First, I systematize the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: 1) they must represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Then I argue that even the most promising attempts to flesh out these constraints have fallen far short. (...)
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  14. L. R. Franklin-Hall (forthcoming). High-Level Explanation and the Interventionist's 'Variables Problem'. British Journal for the Philosophy of Science:axu040.
    The interventionist account of causal explanation, in the version presented by Jim Woodward (2003), has been recently claimed capable of buttressing the widely felt—though poorly understood—hunch that high-level, relatively abstract explanations, of the sort provided by sciences like biology, psychology and economics, are in some cases explanatorily optimal. It is the aim of this paper to show that this is mistaken. Due to a lack of effective constraints on the causal variables at the heart of the interventionist causal-explanatory scheme, as (...)
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  15. Carl Gillett (2007). A Mechanist Manifesto for the Philosophy of Mind: A Third Way for Functionalists. Journal of Philosophical Research 32:21-42.
    One of the main early forms of “functionalism,” developed by writers like Jerry Fodor and William Lycan, focused on “mechanistic” explanation in the special sciences and argued that “functional properties” in psychology were continuous in nature with the special science properties posited in such mechanistic explanations. I dub the latter position“Continuity Functionalism” and use it to critically examine the “Standard Picture” of the metaphysics of functionalism which takes “functional” properties to be second-order properties and claims there are two metaphysical forms (...)
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  16. James Griesemer (2011). Philosophy and Tinkering. Biology and Philosophy 26 (2):269-279.
    I characterize Wimsatt’s approach to philosophy of science as philosophy for science and then briefly consider a theme emerging from his work that informs just one of the many current developments in philosophy of biology that he inspired: scaffolding as a problem of mechanistic explanation for functionalists.
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  17. Peter Hedström & Petri Ylikoski (2011). Analytical Sociology. In Ian C. Jarvie & Jesus Zamoro Bonilla (eds.), The SAGE Handbook of the Philosophy of Social Sciences. SAGE.
  18. Peter Hedström & Petri Ylikoski (2010). Causal Mechanisms in the Social Sciences. Annual Review of Sociology 36:49–67.
    During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea (...)
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  19. Devin Henry (2005). Embryological Models in Ancient Philosophy. Phronesis 50 (1):1-42.
    Historically embryogenesis has been among the most philosophically intriguing phenomena. In this paper I focus on one aspect of biological development that was particularly perplexing to the ancients: self-organisation. For many ancients, the fact that an organism determines the important features of its own development required a special model for understanding how this was possible. This was especially true for Aristotle, Alexander, and Simplicius who all looked to contemporary technology to supply that model. However, they did not all agree on (...)
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  20. Frank Hindriks, Concretization, Explanation, and Mechanisms.
    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 (...)
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  21. Nicholaos Jones (2014). Bowtie Structures, Pathway Diagrams, and Topological Explanation. Erkenntnis 79 (5):1135-1155.
    While mechanistic explanation and, to a lesser extent, nomological explanation are well-explored topics in the philosophy of biology, topological explanation is not. Nor is the role of diagrams in topological explanations. These explanations do not appeal to the operation of mechanisms or laws, and extant accounts of the role of diagrams in biological science explain neither why scientists might prefer diagrammatic representations of topological information to sentential equivalents nor how such representations might facilitate important processes of explanatory reasoning unavailable to (...)
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  22. Marie I. Kaiser & Beate Krickel (forthcoming). The Metaphysics of Constitutive Mechanistic Phenomena. British Journal for the Philosophy of Science.
    The central aim of this paper is to specify the ontological nature of constitutive mechanistic phenomena (i.e. of phenomena that are explained in constitutive mechanistic explanations). After identifying three criteria of adequacy that any plausible approach to constitutive mechanistic phenomena must satisfy, we present four different suggestions, found in the mechanistic literature, of what mechanistic phenomena might be. We argue that none of these suggestions meets the criteria of adequacy. According to our analysis, constitutive mechanistic phenomena are best understood as (...)
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  23. David Michael Kaplan (2012). How to Demarcate the Boundaries of Cognition. Biology and Philosophy 27 (4):545-570.
    Advocates of extended cognition argue that the boundaries of cognition span brain, body, and environment. Critics maintain that cognitive processes are confined to a boundary centered on the individual. All participants to this debate require a criterion for distinguishing what is internal to cognition from what is external. Yet none of the available proposals are completely successful. I offer a new account, the mutual manipulability account, according to which cognitive boundaries are determined by relationships of mutual manipulability between the properties (...)
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  24. David Michael Kaplan (2011). Explanation and Description in Computational Neuroscience. Synthese 183 (3):339-373.
    The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It (...)
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  25. Jaakko Kuorikoski & Petri Ylikoski (2013). How Organization Explains. In Vassilios Karakostas & Dennis Dieks (eds.), Epsa11 Perspectives and Foundational Problems in Philosophy of Science. Springer. 69--80.
  26. Jaakko Kuorikoski & Petri Ylikoski (2010). Explanatory Relevance Across Disciplinary Boundaries: The Case of Neuroeconomics. Journal of Economic Methodology 17 (2):219–228.
    Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.
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  27. Arnon Levy (2013). Three Kinds of New Mechanism. 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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  28. Peter K. Machamer, Lindley Darden & Carl F. Craver (2000). Thinking About Mechanisms. Philosophy of Science 67 (1):1-25.
    The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.
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  29. John Matthewson & Brett Calcott, Mechanistic Explanation Without Mechanisms.
    We provide an account of mechanistic representation and explanation that has several advantages over previous proposals. In our view, explaining mechanistically is not simply giving an explanation of a mechanism. Rather, an explanation is mechanistic because of particular relations that hold between a mechanical representation, or model, and the target of explanation. Under this interpretation, mechanistic explanation is possible even when the explanatory target is not a mechanism. We argue that taking this view is not only coherent and plausible, it (...)
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  30. Dana Matthiessen (forthcoming). Mechanistic Explanation in Systems Biology: Cellular Networks. British Journal for the Philosophy of Science:axv011.
    It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques of (...)
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  31. Nancy L. Maull (1982). Berkeley on the Limits of Mechanistic Explanation. In Colin M. Turbayne (ed.), Berkeley: Critical and Interpretive Essays.
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  32. Roberta L. Millstein (2007). Review of Lindley Darden, Reasoning in Biological Discoveries: Essays on Mechanisms, Interfield Relations, and Anomaly Resolution. [REVIEW] Notre Dame Philosophical Reviews 2007 (7).
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  33. Marcin Miłkowski (forthcoming). Explanatory Completeness and Idealization in Large Brain Simulations: A Mechanistic Perspective. Synthese:1-22.
    The claim defended in the paper is that the mechanistic account of explanation can easily embrace idealization in big-scale brain simulations, and that only causally relevant detail should be present in explanatory models. The claim is illustrated with two methodologically different models: Blue Brain, used for particular simulations of the cortical column in hybrid models, and Eliasmith’s SPAUN model that is both biologically realistic and able to explain eight different tasks. By drawing on the mechanistic theory of computational explanation, I (...)
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  34. Marcin Miłkowski (forthcoming). Satisfaction Conditions in Anticipatory Mechanisms. Biology and Philosophy:1-20.
    The purpose of this paper is to present a general mechanistic framework for analyzing causal representational claims, and offer a way to distinguish genuinely representational explanations from those that invoke representations for honorific purposes. It is usually agreed that rats are capable of navigation because they maintain a cognitive map of their environment. Exactly how and why their neural states give rise to mental representations is a matter of an ongoing debate. I will show that anticipatory mechanisms involved in rats’ (...)
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  35. Marcin Miłkowski (2015). Evaluating Artificial Models of Cognition. Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation ofmodels (...)
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  36. Marcin Miłkowski (2013). Reverse-Engineering in Cognitive-Science. In Marcin Miłkowski & Konrad Talmont-Kaminski (eds.), Regarding the Mind, Naturally: Naturalist Approaches to the Sciences of the Mental. Cambridge Scholars Publishing. 12-29.
    I discuss whether there are some lessons for philosophical inquiry over the nature of simulation to be learnt from the practical methodology of reengineering. I will argue that reengineering serves a similar purpose as simulations in theoretical science such as computational neuroscience or neurorobotics, and that the procedures and heuristics of reengineering help to develop solutions to outstanding problems of simulation.
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  37. Viorel Pâslaru (2014). The Mechanistic Approach of The Theory of Island Biogeography and its Current Relevance. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 45 (1):22-33.
    Philosophers of science have examined The Theory of Island Biogeography by Robert MacArthur and E. O. Wilson (1967) mainly due to its important contribution to modeling in ecology, but they have not examined it as a representative case of ecological explanation. In this paper, I scrutinize the type of explanation used in this paradigmatic work of ecology. I describe the philosophy of science of MacArthur and Wilson and show that it is mechanistic. Based on this account and in light of (...)
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  38. Johannes Persson (2012). Mechanistic Explanation in Social Contexts: Elster and the Problem of Local Scientific Growth. Social Epistemology 26 (1):105-114.
    Jon Elster worries about the explanatory power of the social sciences. His main concern is that they have so few well-established laws. Elster develops an interesting substitute: a special kind of mechanism designed to fill the explanatory gap between laws and mere description. However, his mechanisms suffer from a characteristic problem that I will explore in this article. As our causal knowledge of a specific problem grows we might come to know too much to make use of an Elsterian mechanism (...)
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  39. Johannes Persson (2010). Activity-Based Accounts of Mechanism and the Threat of Polygenic Effects. Erkenntnis 72 (1):135 - 149.
    Accounts of ontic explanation have often been devised so as to provide an understanding of mechanism and of causation. Ontic accounts differ quite radically in their ontologies, and one of the latest additions to this tradition proposed by Peter Machamer, Lindley Darden and Carl Craver reintroduces the concept of activity. In this paper I ask whether this influential and activity-based account of mechanisms is viable as an ontic account. I focus on polygenic scenarios—scenarios in which the causal truths depend on (...)
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  40. Johannes Persson (2005). Tropes as Mechanisms. Foundations of Science 10 (4):371-393.
    This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of (...)
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  41. Johannes Persson & Petri Ylikoski (eds.) (2007). Rethinking Explanation. Springer.
    This book highlights some of the conceptual problems that still need to be solved and points out a number of fresh philosophical ideas to explore.
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  42. Gualtiero Piccinini & Carl Craver (2011). Integrating Psychology and Neuroscience: Functional Analyses as Mechanism Sketches. [REVIEW] 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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  43. Thomas Reydon (2009). How to Fix Kind Membership: A Problem for Hpc Theory and a Solution. Philosophy of Science 76 (5):724-736.
    Natural kinds are often contrasted with other kinds of scientific kinds, especially functional kinds, because of a presumed categorical difference in explanatory value: supposedly, natural kinds can ground explanations, while other kinds of kinds cannot. I argue against this view of natural kinds by examining a particular type of explanation—mechanistic explanation—and showing that functional kinds do the same work there as traditionally recognized natural kinds are supposed to do in “standard” scientific explanations. Breaking down this categorical distinction between traditional natural (...)
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  44. Wesley C. Salmon (1985). Conflicting Conceptions of Scientific Explanation. Journal of Philosophy 82 (11):651-654.
  45. Bertold Schweitzer (forthcoming). Modelling Mechanisms of Democratic Transition in the Arab Uprisings. Middle East Critique 24 (1).
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  46. Bertold Schweitzer (2015). From Malfunction to Mechanism. Philosophia Scientiæ 19 (1):21-34.
    Le dysfonctionnement, la défectuosité et les erreurs sont des phénomènes qui peuvent aider à mieux comprendre les entités affectées par ces incidents. L’analyse approfondie du fonctionnement et du dysfonctionnement facilite en particulier la découverte, l’explication et la modélisation théorique des structures, fonctions et mécanismes propres à un système. Dans certains cas, les dysfonctionnements sont le seul moyen d’accéder aux processus internes d’un certain système. Le présent essai analyse les méthodes de diverses disciplines tenant compte de dysfonctionnements tels que les mutations, (...)
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  47. Bertold Schweitzer (2013). ‘Vom Fehler im Gegenstand zur Theorie über den Gegenstand’: Wissenschaftstheorie und interdisziplinäres Arbeiten. In Michael Jungert, Elsa Romfeld, Thomas Sukopp & Uwe Voigt (eds.), Interdisziplinarität: Theorie, Praxis, Probleme. Wissenschaftliche Buchgesellschaft. 109-126.
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  48. Johanna Seibt (2009). Forms of Emergent Interaction in General Process Theory. Synthese 166 (3):479 - 512.
    General Process Theory (GPT) is a new (non-Whiteheadian) process ontology. According to GPT the domains of scientific inquiry and everyday practice consist of configurations of ‘goings-on’ or ‘dynamics’ that can be technically defined as concrete, dynamic, non-particular individuals called general processes. The paper offers a brief introduction to GPT in order to provide ontological foundations for research programs such as interactivism that centrally rely on the notions of ‘process,’ ‘interaction,’ and ‘emergence.’ I begin with an analysis of our common sense (...)
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  49. Michael J. Shaffer & Jeffery Oakley (2005). Some Epistemological Concerns About Dissociative Identity Disorder and Diagnostic Practices in Psychology. Philosophical Psychology 18 (1):1-29.
    In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...)
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  50. Robert A. Skipper & Roberta L. Millstein (2005). Thinking About Evolutionary Mechanisms: Natural Selection. Studies in History and Philosophy of Biological and Biomedical Sciences 36 (2):327-347.
    This paper explores whether natural selection, a putative evolutionary mechanism, and a main one at that, can be characterized on either of the two dominant conceptions of mechanism, due to Glennan and the team of Machamer, Darden, and Craver, that constitute the “new mechanistic philosophy.” The results of the analysis are that neither of the dominant conceptions of mechanism adequately captures natural selection. Nevertheless, the new mechanistic philosophy possesses the resources for an understanding of natural selection under the rubric.
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