Search results for 'mechanistic explanation' (try it on Scholar)

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  1. F. Michael Akeroyd (2008). Mechanistic Explanation Versus Deductive-Nomological Explanation. Foundations of Chemistry 10 (1):39-48.score: 180.0
    This paper discusses the important paper by Paul Thagard on the pathway version of mechanistic explanation that is currently used in chemical explanation. The author claims that this method of explanation has a respectable pedigree and can be traced back to the Chemical Revolution in the arguments used by the Lavoisier School in their theoretical duels with Richard Kirwan, the proponent of a revised phlogistonian theory. Kirwan believed that complex chemical reactions could be explained by recourse (...)
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  2. 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.score: 180.0
    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 (...)
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  3. David Barrett (2014). Functional Analysis and Mechanistic Explanation. Synthese 191 (12):2695-2714.score: 180.0
    Piccinini and Craver (Synthese 183:283–311, 2011) argue for the surprising view that psychological explanation, properly understood, is a species of mechanistic explanation. This contrasts with the ‘received view’ (due, primarily, to Cummins and Fodor) which maintains a sharp distinction between psychological explanation and mechanistic explanation. The former is typically construed as functional analysis, the analysis of some psychological capacity into an organized series of subcapacities without specifying any of the structural features that underlie the (...)
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  4. Nick Chater (2014). Cognitive Science as an Interface Between Rational and Mechanistic Explanation. Topics in Cognitive Science 6 (1):331-337.score: 174.0
    Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). (...)
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  5. Cory D. Wright (2012). Mechanistic Explanation Without the Ontic Conception. European Journal of Philosophy of Science 2 (3):375-394.score: 162.0
    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, (...)
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  6. Johannes Persson (2012). Mechanistic Explanation in Social Contexts: Elster and the Problem of Local Scientific Growth. Social Epistemology 26 (1):105-114.score: 156.0
    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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  7. John Matthewson & Brett Calcott, Mechanistic Explanation Without Mechanisms.score: 132.0
    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 (...)
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  8. D. Benjamin Barros (2013). Negative Causation in Causal and Mechanistic Explanation. Synthese 190 (3):449-469.score: 132.0
    Instances of negative causation—preventions, omissions, and the like—have long created philosophical worries. In this paper, I argue that concerns about negative causation can be addressed in the context of causal explanation generally, and mechanistic explanation specifically. The gravest concern about negative causation is that it exacerbates the problem of causal promiscuity—that is, the problem that arises when a particular account of causation identifies too many causes for a particular effect. In the explanatory context, the problem of promiscuity (...)
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  9. Sasan Haghighi, The Role of Philosophy in Cognitive Science: Normativity, Generality, Mechanistic Explanation. OZSW 2013 Rotterdam.score: 132.0
    ID: 89 / Parallel 4k: 2 Single paper Topics: Philosophy of mind, Philosophy of science Keywords: Cognitive Science, Cognitive Neuroscience, Mechanistic explanations, Reductionism, Normativity, Generality, Emerging School of Philosophers of Science. The role of philosophy in cognitive science: mechanistic explanations, normativity, generality Mohammadreza Haghighi Fard Leiden University, Netherlands, The; haghighiphil@aol.com Introduction -/- Cognitive science, as an interdisciplinary research endeavour, seeks to explain mental activities such as reasoning, remembering, language use, and problem solving, and the explanations it advances commonly (...)
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  10. Jonathan Waskan (2011). Mechanistic Explanation at the Limit. Synthese 183 (3):389-408.score: 128.0
    Resurgent interest in both mechanistic and counterfactual theories of explanation has led to a fair amount of discussion regarding the relative merits of these two approaches. James Woodward is currently the pre-eminent counterfactual theorist, and he criticizes the mechanists on the following grounds: Unless mechanists about explanation invoke counterfactuals, they cannot make sense of claims about causal interactions between mechanism parts or of causal explanations put forward absent knowledge of productive mechanisms. He claims that these shortfalls can (...)
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  11. Ingo Brigandt (forthcoming). Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation. In P.-A. Braillard and C. Malaterre (ed.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer.score: 126.0
    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 (...)
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  12. James Woodward (2013). Mechanistic Explanation: Its Scope and Limits. Aristotelian Society Supplementary Volume 87 (1):39-65.score: 120.0
    This paper explores the question of whether all or most explanations in biology are, or ideally should be, ‘mechanistic’. I begin by providing an account of mechanistic explanation, making use of the interventionist ideas about causation I have developed elsewhere. This account emphasizes the way in which mechanistic explanations, at least in the biological sciences, integrate difference-making and spatio-temporal information, and exhibit what I call fine-tunedness of organization. I also emphasize the role played by modularity conditions (...)
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  13. William Bechtel (2009). Looking Down, Around, and Up: Mechanistic Explanation in Psychology. Philosophical Psychology 22 (5):543-564.score: 120.0
    Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, (...)
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  14. F. J. Bruggeman, H. V. Westerhoff & F. C. Boogerd (2002). Biocomplexity: A Pluralist Research Strategy is Necessary for a Mechanistic Explanation of the "Live" State. Philosophical Psychology 15 (4):411 – 440.score: 120.0
    The biological sciences study (bio)complex living systems. Research directed at the mechanistic explanation of the "live" state truly requires a pluralist research program, i.e. BioComplexity research. The program should apply multiple intra-level and inter-level theories and methodologies. We substantiate this thesis with analysis of BioComplexity: metabolic and modular control analysis of metabolic pathways, emergence of oscillations, and the analysis of the functioning of glycolysis.
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  15. Phyllis Illari (2013). Mechanistic Explanation: Integrating the Ontic and Epistemic. Erkenntnis 78 (2):237-255.score: 120.0
    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 (...)
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  16. Denis Forest (2009). Comments on William Bechtel's “Looking Down, Around, and Up: Mechanistic Explanation in Psychology”. Philosophical Psychology 22 (5):565-573.score: 120.0
    The first part of this paper deals with the relations between mechanistic explanation and reduction. It is argued that there is no insuperable conflict between the two, but that the mechanistic framework adds requirements that are not acknowledged in the model of property reduction. The second part concerns the relations between organization and environmental factors. Internal organization may be so tightly linked to external context that both have to be considered together.
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  17. David M. Kaplan & William Bechtel (2011). Dynamical Models: An Alternative or Complement to Mechanistic Explanations? Topics in Cognitive Science 3 (2):438-444.score: 116.0
    Abstract While agreeing that dynamical models play a major role in cognitive science, we reject Stepp, Chemero, and Turvey's contention that they constitute an alternative to mechanistic explanations. We review several problems dynamical models face as putative explanations when they are not grounded in mechanisms. Further, we argue that the opposition of dynamical models and mechanisms is a false one and that those dynamical models that characterize the operations of mechanisms overcome these problems. By briefly considering examples involving the (...)
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  18. Stuart Glennan (2002). Rethinking Mechanistic Explanation. Proceedings of the Philosophy of Science Association 2002 (3):S342-353.score: 116.0
    Philosophers of science typically associate the causal-mechanical view of scientific explanation with the work of Railton and Salmon. In this paper I shall argue that the defects of this view arise from an inadequate analysis of the concept of mechanism. I contrast Salmon's account of mechanisms in terms of the causal nexus with my own account of mechanisms, in which mechanisms are viewed as complex systems. After describing these two concepts of mechanism, I show how the complex-systems approach avoids (...)
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  19. William Bechtel & Adele Abrahamsen (2005). Mechanistic Explanation and the Nature-Nurture Controversy. Bulletin d'Histoire Et d'pistmologie Des Sciences de La Vie 12:75-100.score: 114.0
    Both in biology and psychology there has been a tendency on the part of many investigators to focus solely on the mature organism and ignore development. There are many reasons for this, but an important one is that the explanatory framework often invoked in the life sciences for understanding a given phenomenon, according to which explanation consists in identifying the mechanism that produces that phenomenon, both makes it possible to side-step the development issue and to provide inadequate resources for (...)
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  20. Jeroen de Ridder (2006). Mechanistic Artefact Explanation. Studies in History and Philosophy of Science Part A 37 (1):81-96.score: 114.0
    One thing about technical artefacts that needs to be explained is how their physical make-up, or structure, enables them to fulfil the behaviour associated with their function, or, more colloquially, how they work. In this paper I develop an account of such explanations based on the familiar notion of mechanistic explanation. To accomplish this, I (1) outline two explanatory strategies that provide two different types of insight into an artefact’s functioning, and (2) show how human action inevi- tably (...)
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  21. Samuel Schindler (2013). Mechanistic Explanation: Asymmetry Lost. In Karakostas and Dieks (ed.), “Recent Progress in Philosophy of Science: Perspectives and Foundational Problems”. Springer.score: 114.0
    In a recent book and an article, Carl Craver construes the relations between different levels of a mechanism, which he also refers to as constitutive relations, in terms of mutual manipulability (MM). Interpreted metaphysically, MM implies that inter-level relations are symmetrical. MM thus violates one of the main desiderata of scientific explanation, namely explanatory asymmetry. Parts of Craver’s writings suggest a metaphysical interpretation of MM, and Craver explicitly commits to constitutive relationships being symmetrical. The paper furthermore explores the option (...)
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  22. Joachim Frans & Erik Weber (2014). Mechanistic Explanation and Explanatory Proofs in Mathematics. Philosophia Mathematica 22 (2):231-248.score: 114.0
    Although there is a consensus among philosophers of mathematics and mathematicians that mathematical explanations exist, only a few authors have proposed accounts of explanation in mathematics. These accounts fit into the unificationist or top-down approach to explanation. We argue that these models can be complemented by a bottom-up approach to explanation in mathematics. We introduce the mechanistic model of explanation in science and discuss the possibility of using this model in mathematics, arguing that using it (...)
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  23. Vivian M. Weil (1980). Intentional and Mechanistic Explanation. Philosophy and Phenomenological Research 40 (June):459-473.score: 114.0
  24. Cory D. Wright & William P. Bechtel (2007). Mechanisms and Psychological Explanation. In Paul Thagard (ed.), Philosophy of Psychology and Cognitive Science. Elsevier.score: 108.0
    As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in (...)
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  25. Carlos Zednik (2011). The Nature of Dynamical Explanation. Philosophy of Science 78 (2):238-263.score: 108.0
    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, (...)
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  26. Fred C. Boogerd, Frank J. Bruggeman & Robert C. Richardson (2013). Mechanistic Explanations and Models in Molecular Systems Biology. Foundations of Science 18 (4):725-744.score: 108.0
    Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation and development (...)
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  27. Georg Theiner (2013). Transactive Memory Systems: A Mechanistic Analysis of Emergent Group Memory. Review of Philosophy and Psychology 4 (1):65-89.score: 108.0
    Wegner, Giuliano, and Hertel (1985) defined the notion of a transactive memory system (TMS) as a group level memory system that “involves the operation of the memory systems of the individuals and the processes of communication that occur within the group (p. 191). Those processes are the collaborative procedures (“transactions”) by which groups encode, store, and retrieve information that is distributed among their members. Over the past 25+ years, the conception of a TMS has progressively garnered an increased interest among (...)
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  28. Mitchell Herschbach (2012). On the Role of Social Interaction in Social Cognition: A Mechanistic Alternative to Enactivism. [REVIEW] Phenomenology and the Cognitive Sciences 11 (4):467-486.score: 102.0
    Researchers in the enactivist tradition have recently argued that social interaction can constitute social cognition, rather than simply serve as the context for social cognition. They contend that a focus on social interaction corrects the overemphasis on mechanisms inside the individual in the explanation of social cognition. I critically assess enactivism’s claims about the explanatory role of social interaction in social cognition. After sketching the enactivist approach to cognition in general and social cognition in particular, I identify problems with (...)
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  29. Gualtiero Piccinini & Carl Craver (2011). Integrating Psychology and Neuroscience: Functional Analyses as Mechanism Sketches. [REVIEW] Synthese 183 (3):283-311.score: 96.0
    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, (...)
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  30. Holly Andersen (2012). The Case for Regularity in Mechanistic Causal Explanation. Synthese 189 (3):415-432.score: 96.0
    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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  31. Gualtiero Piccinini (2007). Computational Explanation and Mechanistic Explanation of Mind. In Francesco Ferretti, Massimo Marraffa & Mario De Caro (eds.), Cartographies of the Mind: The Interface Between Philosophy and Cognitive Science. Springer. 343-353.score: 96.0
    According to the computational theory of mind (CTM), mental capacities are explained by inner computations, which in biological organisms are realized in the brain. Computational explanation is so popular and entrenched that it’s common for scientists and philosophers to assume CTM without argument.
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  32. Carl F. Craver (2008). Physical Law and Mechanistic Explanation in the Hodgkin and Huxley Model of the Action Potential. Philosophy of Science 75 (5):1022-1033.score: 96.0
    Hodgkin and Huxley’s model of the action potential is an apparent dream case of covering‐law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to explain it or that Hodgkin and Huxley were wrong. I (...)
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  33. Alexander Reutlinger (2011). What's Wrong with the Pragmatic-Ontic Account of Mechanistic Explanation?. In. In Dennis Dieks, Wenceslao Gonzalo, Thomas Uebel, Stephan Hartmann & Marcel Weber (eds.), Explanation, Prediction, and Confirmation. Springer. 141--152.score: 96.0
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  34. William Bechtel & Adele Abrahamsen (2010). Dynamic Mechanistic Explanation: Computational Modeling of Circadian Rhythms as an Exemplar for Cognitive Science. Studies in History and Philosophy of Science Part A 41 (3):321-333.score: 92.0
    Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction with their (...)
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  35. Raoul Gervais & Erik Weber (2013). Plausibility Versus Richness in Mechanistic Models. Philosophical Psychology 26 (1):139-152.score: 92.0
    In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives (...)
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  36. William Bechtel & Mitchell Herschbach (2010). Philosophy of the Cognitive Sciences. In Fritz Allhoff (ed.), Philosophies of the Sciences. Wiley-Blackwell. 239--261.score: 90.0
    Cognitive science is an interdisciplinary research endeavor focusing on human cognitive phenomena such as memory, language use, and reasoning. It emerged in the second half of the 20th century and is charting new directions at the beginning of the 21st century. This chapter begins by identifying the disciplines that contribute to cognitive science and reviewing the history of the interdisciplinary engagements that characterize it. The second section examines the role that mechanistic explanation plays in cognitive science, while the (...)
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  37. Arno G. Wouters (2007). Design Explanation: Determining the Constraints on What Can Be Alive. [REVIEW] Erkenntnis 67 (1):65-80.score: 90.0
    This paper is concerned with reasonings that purport to explain why certain organisms have certain traits by showing that their actual design is better than contrasting designs. Biologists call such reasonings ‘functional explanations’. To avoid confusion with other uses of that phrase, I call them ‘design explanations’. This paper discusses the structure of design explanations and how they contribute to scientific understanding. Design explanations are contrastive and often compare real organisms to hypothetical organisms that cannot possibly exist. They are not (...)
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  38. Machiel Keestra (2014). Sculpting the Space of Actions. Explaining Human Action by Integrating Intentions and Mechanisms. Dissertation, University of Amsterdamscore: 90.0
    How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations (...)
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  39. Ernest Nagel (1951). Mechanistic Explanation and Organismic Biology. Philosophy and Phenomenological Research 11 (3):327-338.score: 90.0
  40. William Bechtel (2012). Understanding Endogenously Active Mechanisms: A Scientific and Philosophical Challenge. [REVIEW] European Journal for Philosophy of Science 2 (2):233-248.score: 90.0
    Abstract Although noting the importance of organization in mechanisms, the new mechanistic philosophers of science have followed most biologists in focusing primarily on only the simplest mode of organization in which operations are envisaged as occurring sequentially. Increasingly, though, biologists are recognizing that the mechanisms they confront are non-sequential and the operations nonlinear. To understand how such mechanisms function through time, they are turning to computational models and tools of dynamical systems theory. Recent research on circadian rhythms addressing both (...)
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  41. Fabrizzio Guerrero Mc Manus (2012). Development and Mechanistic Explanation. Studies in History and Philosophy of Science Part C 43 (2):532-541.score: 90.0
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  42. Johannes Persson (2010). Activity-Based Accounts of Mechanism and the Threat of Polygenic Effects. Erkenntnis 72 (1):135 - 149.score: 90.0
    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 (...)
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  43. Melinda Bonnie Fagan (2012). The Joint Account of Mechanistic Explanation. Philosophy of Science 79 (4):448-472.score: 90.0
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  44. Melinda Bonnie Fagan (2012). The Joint Account of Mechanistic Explanation. Philosophy of Science 79 (4):448-472.score: 90.0
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  45. Max Kistler, Mechanistic Explanation and Causality.score: 90.0
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  46. Markus I. Eronen (2011). Replacing Functional Reduction with Mechanistic Explanation. Philosophia Naturalis 47 (1-2):1-2.score: 90.0
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  47. Claudio Mattiussi (forthcoming). Can an Engineer Fix an Immune System?–Rethinking Theoretical Biology. Acta Biotheoretica.score: 90.0
    In an instant classic paper (Lazebnik, in Cancer Cell 2(3); 2002 : 179–182) biologist Yuri Lazebnik deplores the poor effectiveness of the approach adopted by biologists to understand and “fix” biological systems. Lazebnik suggests that to remedy this state of things biologist should take inspiration from the approach used by engineers to design, understand, and troubleshoot technological systems. In the present paper I substantiate Lazebnik’s analysis by concretely showing how to apply the engineering approach to biological problems. I use an (...)
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  48. Nancy L. Maull (1982). Berkeley on the Limits of Mechanistic Explanation. In Colin M. Turbayne (ed.), Berkeley: Critical and Interpretive Essays.score: 90.0
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  49. William Bechtel & Cory D. Wright (2009). What is Psychological Explanation? In P. Calvo & J. Symons (eds.), Routledge Companion to the Philosophy of Psychology. Routledge. 113--130.score: 84.0
    Due to the wide array of phenomena that are of interest to them, psychologists offer highly diverse and heterogeneous types of explanations. Initially, this suggests that the question "What is psychological explanation?" has no single answer. To provide appreciation of this diversity, we begin by noting some of the more common types of explanations that psychologists provide, with particular focus on classical examples of explanations advanced in three different areas of psychology: psychophysics, physiological psychology, and information-processing psychology. To analyze (...)
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