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William Bechtel [172]William P. Bechtel [35]
  1.  6
    Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research.William Bechtel & Robert C. Richardson - 1993 - 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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  2.  5
    Mental Mechanisms: Philosophical Perspectives on Cognitive Neuroscience.William Bechtel - 2007 - Psychology Press.
    A variety of scientific disciplines have set as their task explaining mental activities, recognizing that in some way these activities depend upon our brain. But, until recently, the opportunities to conduct experiments directly on our brains were limited. As a result, research efforts were split between disciplines such as cognitive psychology, linguistics, and artificial intelligence that investigated behavior, while disciplines such as neuroanatomy, neurophysiology, and genetics experimented on the brains of non-human animals. In recent decades these disciplines integrated, and with (...)
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  3. Explanation: A Mechanist Alternative.William Bechtel - 2005 - Studies in History and Philosophy of Biol and Biomed Sci 36 (2):421--441.
    Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ dia- grams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations (...)
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  4.  65
    Explanation: A Mechanist Alternative.William Bechtel & Adele Abrahamsen - 2005 - Studies in History and Philosophy of Biological and Biomedical Sciences 36 (2):421-441.
    Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...)
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  5. Philosophy of Mind: An Overview for Cognitive Science.William Bechtel - 1988 - Lawrence Erlbaum.
    Specifically designed to make the philosophy of mind intelligible to those not trained in philosophy, this book provides a concise overview for students and researchers in the cognitive sciences. Emphasizing the relevance of philosophical work to investigations in other cognitive sciences, this unique text examines such issues as the meaning of language, the mind-body problem, the functionalist theories of cognition, and intentionality. As he explores the philosophical issues, Bechtel draws connections between philosophical views and theoretical and experimental work in such (...)
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  6. Top-Down Causation Without Top-Down Causes.Carl F. Craver & William Bechtel - 2007 - Biology and Philosophy 22 (4):547-563.
    We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...)
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  7.  3
    Discovering Cell Mechanisms: The Creation of Modern Cell Biology.William Bechtel - 2005 - Cambridge University Press.
    Between 1940 and 1970 pioneers in the new field of cell biology discovered the operative parts of cells and their contributions to cell life. They offered mechanistic accounts that explained cellular phenomena by identifying the relevant parts of cells, the biochemical operations they performed, and the way in which these parts and operations were organised to accomplish important functions. Cell biology was a revolutionary science but in this book it also provides fuel for yet another revolution, one that focuses on (...)
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  8. Abstraction and the Organization of Mechanisms.Arnon Levy & William Bechtel - 2013 - Philosophy of Science 80 (2):241-261.
    Proponents of mechanistic explanation all acknowledge the importance of organization. But they have also tended to emphasize specificity with respect to parts and operations in mechanisms. We argue that in understanding one important mode of organization—patterns of causal connectivity—a successful explanatory strategy abstracts from the specifics of the mechanism and invokes tools such as those of graph theory to explain how mechanisms with a particular mode of connectivity will behave. We discuss the connection between organization, abstraction, and mechanistic explanation and (...)
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  9. Multiple Realizability Revisited: Linking Cognitive and Neural States.William Bechtel - 1999 - Philosophy of Science 66 (2):175-207.
    The claim of the multiple realizability of mental states by brain states has been a major feature of the dominant philosophy of mind of the late 20th century. The claim is usually motivated by evidence that mental states are multiply realized, both within humans and between humans and other species. We challenge this contention by focusing on how neuroscientists differentiate brain areas. The fact that they rely centrally on psychological measures in mapping the brain and do so in a comparative (...)
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  10. Mechanism and Biological Explanation.William Bechtel - 2011 - Philosophy of Science 78 (4):533-557.
    This article argues that the basic account of mechanism and mechanistic explanation, involving sequential execution of qualitatively characterized operations, is itself insufficient to explain biological phenomena such as the capacity of living organisms to maintain themselves as systems distinct from their environment. This capacity depends on cyclic organization, including positive and negative feedback loops, which can generate complex dynamics. Understanding cyclically organized mechanisms with complex dynamics requires coordinating research directed at decomposing mechanisms into parts and operations with research using computational (...)
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  11. Dynamic Mechanistic Explanation: Computational Modeling of Circadian Rhythms as an Exemplar for Cognitive Science.William Bechtel & Adele Abrahamsen - 2010 - Studies in History and Philosophy of Science Part A 41 (3):321-333.
    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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  12.  2
    Connectionism and the Mind.William Bechtel & Adele Abrahamsen - 1991 - Wiley-Blackwell.
    Something remarkable is happening in the cognitive sciences. After a quarter of a century of cognitive models that were inspired by the metaphor of the digital computer, the newest cognitive models are inspired by the properties of the brain itself. Variously referred to as connectionist, parallel distributed processing, or neutral network models, they explore the idea that complex intellectual operations can be carried out by large networks of simple, neuron-like units. The units themselves are identical, very low-level and 'stupid'. Intelligent (...)
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  13. Mechanism, Autonomy and Biological Explanation.Leonardo Bich & William Bechtel - 2021 - Biology and Philosophy 36 (6):1-27.
    The new mechanists and the autonomy approach both aim to account for how biological phenomena are explained. One identifies appeals to how components of a mechanism are organized so that their activities produce a phenomenon. The other directs attention towards the whole organism and focuses on how it achieves self-maintenance. This paper discusses challenges each confronts and how each could benefit from collaboration with the other: the new mechanistic framework can gain by taking into account what happens outside individual mechanisms, (...)
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  14. Control Mechanisms: Explaining the Integration and Versatility of Biological Organisms.Leonardo Bich & William Bechtel - 2022 - Adaptive Behavior.
    Living organisms act as integrated wholes to maintain themselves. Individual actions can each be explained by characterizing the mechanisms that perform the activity. But these alone do not explain how various activities are coordinated and performed versatilely. We argue that this depends on a specific type of mechanism, a control mechanism. We develop an account of control by examining several extensively studied control mechanisms operative in the bacterium E. coli. On our analysis, what distinguishes a control mechanism from other mechanisms (...)
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  15. Mental Mechanisms: Philosophical Perspectives on the Sciences of Cognition and the Brain.William P. Bechtel - manuscript
    1. The Naturalistic Turn in Philosophy of Science 2. The Framework of Mechanistic Explanation: Parts, Operations, and Organization 3. Representing and Reasoning About Mechanisms 4. Mental Mechanisms: Mechanisms that Process Information 5. Discovering Mental Mechanisms 6 . Summary.
     
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  16. Discovering Complexity.William Bechtel, Robert C. Richardson & Scott A. Kleiner - 1996 - History and Philosophy of the Life Sciences 18 (3):363-382.
  17. Discovering Cell Mechanisms: The Creation of Modern Cell Biology.William Bechtel - 2007 - Journal of the History of Biology 40 (1):185-187.
    Between 1940 and 1970 pioneers in the new field of cell biology discovered the operative parts of cells and their contributions to cell life. They offered mechanistic accounts that explained cellular phenomena by identifying the relevant parts of cells, the biochemical operations they performed, and the way in which these parts and operations were organised to accomplish important functions. Cell biology was a revolutionary science but in this book it also provides fuel for yet another revolution, one that focuses on (...)
     
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  18. Dynamical Models: An Alternative or Complement to Mechanistic Explanations?David M. Kaplan & William Bechtel - 2011 - Topics in Cognitive Science 3 (2):438-444.
    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 generation (...)
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  19. Investigating Neural Representations: The Tale of Place Cells.William Bechtel - 2016 - Synthese 193 (5):1287-1321.
    While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example involving (...)
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  20.  77
    Rethinking Causality in Biological and Neural Mechanisms: Constraints and Control.Jason Winning & William Bechtel - 2018 - Minds and Machines 28 (2).
    Existing accounts of mechanistic causation are not suited for understanding causation in biological and neural mechanisms because they do not have the resources to capture the unique causal structure of control heterarchies. In this paper, we provide a new account on which the causal powers of mechanisms are grounded by time-dependent, variable constraints. Constraints can also serve as a key bridge concept between the mechanistic approach to explanation and underappreciated work in theoretical biology that sheds light on how biological systems (...)
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  21.  93
    Explicating Top-­‐Down Causation Using Networks and Dynamics.William Bechtel - 2017 - Philosophy of Science 84 (2):253-274.
    In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and Bechtel defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and causation as solely an intra-level relation. Craver and Bechtel, however, provided insufficient specification as to when entities constitute a higher-level mechanism. In this paper I appeal to graph-theoretic representations of networks that are now widely employed in systems biology and neuroscience to (...)
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  22. Looking Down, Around, and Up: Mechanistic Explanation in Psychology.William Bechtel - 2009 - Philosophical Psychology 22 (5):543-564.
    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, they frequently (...)
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  23. The Non-­‐Redundant Contributions of Marr’s Three Levels of Analysis for Explaining Information Processing Mechanisms.William Bechtel & Oron Shagrir - 2015 - Topics in Cognitive Science 7 (2):312-322.
    Are all three of Marr's levels needed? Should they be kept distinct? We argue for the distinct contributions and methodologies of each level of analysis. It is important to maintain them because they provide three different perspectives required to understand mechanisms, especially information-processing mechanisms. The computational perspective provides an understanding of how a mechanism functions in broader environments that determines the computations it needs to perform. The representation and algorithmic perspective offers an understanding of how information about the environment is (...)
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  24.  95
    Grounding Cognition: Heterarchical Control Mechanisms in Biology.William Bechtel & Leonardo Bich - 2021 - Philosophical Transactions of the Royal Society B: Biological Sciences 376 (1820).
    We advance an account that grounds cognition, specifically decision-making, in an activity all organisms as autonomous systems must perform to keep themselves viable—controlling their production mechanisms. Production mechanisms, as we characterize them, perform activities such as procuring resources from their environment, putting these resources to use to construct and repair the organism's body and moving through the environment. Given the variable nature of the environment and the continual degradation of the organism, these production mechanisms must be regulated by control mechanisms (...)
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  25.  66
    Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity.Sara Green, Maria Şerban, Raphael Scholl, Nicholaos Jones, Ingo Brigandt & William Bechtel - 2018 - Synthese 195 (4):1751-1777.
    The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from (...)
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  26. Thinking Dynamically About Biological Mechanisms: Networks of Coupled Oscillators. [REVIEW]William Bechtel & Adele A. Abrahamsen - 2013 - Foundations of Science 18 (4):707-723.
    Explaining the complex dynamics exhibited in many biological mechanisms requires extending the recent philosophical treatment of mechanisms that emphasizes sequences of operations. To understand how nonsequentially organized mechanisms will behave, scientists often advance what we call dynamic mechanistic explanations. These begin with a decomposition of the mechanism into component parts and operations, using a variety of laboratory-based strategies. Crucially, the mechanism is then recomposed by means of computational models in which variables or terms in differential equations correspond to properties of (...)
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  27. Representations and Cognitive Explanations: Assessing the Dynamicist Challenge in Cognitive Science.William Bechtel - 1998 - Cognitive Science 22 (3):295-317.
    Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that (...)
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  28.  22
    Connectionism and the Mind: An Introduction to Parallel Processing in Networks.David Pickles, William Bechtel & Adele Abrahamson - 1992 - Philosophical Quarterly 42 (166):101.
  29. Levels of Description and Explanation in Cognitive Science.William Bechtel - 1994 - Minds and Machines 4 (1):1-25.
    The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis of processes at (...)
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  30. Complex Biological Mechanisms: Cyclic, Oscillatory, and Autonomous.William Bechtel & Adele Abrahamsen - unknown
    The mechanistic perspective has dominated biological disciplines such as biochemistry, physiology, cell and molecular biology, and neuroscience, especially during the 20th century. The primary strategy is reductionist: organisms are to be decomposed into component parts and operations at multiple levels. Researchers adopting this perspective have generated an enormous body of information about the mechanisms of life at scales ranging from the whole organism down to genetic and other molecular operations.
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  31. Mechanisms and Psychological Explanation.Cory Wright & William Bechtel - 2007 - In Paul Thagard (ed.), Handbook of the Philosophy of Psychology and Cognitive Science. Elsevier.
    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 which mechanistic approaches serve to bridge levels rather than (...)
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  32.  48
    Can Mechanistic Explanation Be Reconciled with Scale-Free Constitution and Dynamics?William Bechtel - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 53:84-93.
  33. Philosophy and the Neurosciences: A Reader.William P. Bechtel, Pete Mandik, Jennifer Mundale & Robert S. Stufflebeam (eds.) - 2001 - Blackwell.
    2. Daugman, J. G. Brain metaphor and brain theory 3. Mundale, J. Neuroanatomical Foundations of Cognition: Connecting the Neuronal Level with the Study of Higher Brain Areas.
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  34.  23
    Integrating Scientific Disciplines.William Bechtel (ed.) - 1986 - University of Chicago Press.
  35. Reducing Psychology While Maintaining its Autonomy Via Mechanistic Explanations.William Bechtel - 2007 - In M. Schouten & H. L. De Joong (eds.), The Matter of the Mind: Philosophical Essays on Psychology, Neuroscience and Reduction. Blackwell.
    Arguments for the autonomy of psychology or other higher-level sciences have often taken the form of denying the possibility of reduction. The form of reduction most proponents and critics of the autonomy of psychology have in mind is theory reduction. Mechanistic explanations provide a different perspective. Mechanistic explanations are reductionist insofar as they appeal to lower-level entities—the component parts of a mechanism and their operations— to explain a phenomenon. However, unlike theory reductions, mechanistic explanations also recognize the fundamental role of (...)
     
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  36.  5
    Connectionism and the Mind: Parallel Processing, Dynamics, and Evolution in Networks.William Bechtel & Adele Abrahamsen - 2002 - Wiley-Blackwell.
    Connectionism and the Mind provides a clear and balanced introduction to connectionist networks and explores theoretical and philosophical implications. Much of this discussion from the first edition has been updated, and three new chapters have been added on the relation of connectionism to recent work on dynamical systems theory, artificial life, and cognitive neuroscience. Read two of the sample chapters on line: Connectionism and the Dynamical Approach to Cognition: http://www.blackwellpublishing.com/pdf/bechtel.pdf Networks, Robots, and Artificial Life: http://www.blackwellpublishing.com/pdf/bechtel2.pdf.
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  37. Generalization and Discovery by Assuming Conserved Mechanisms: Cross‐Species Research on Circadian Oscillators.William Bechtel - 2009 - Philosophy of Science 76 (5):762-773.
    In many domains of biology, explanation takes the form of characterizing the mechanism responsible for a particular phenomenon in a specific biological system. How are such explanations generalized? One important strategy assumes conservation of mechanisms through evolutionary descent. But conservation is seldom complete. In the case discussed, the central mechanism for circadian rhythms in animals was first identified in Drosophila and then extended to mammals. Scientists' working assumption that the clock mechanisms would be conserved both yielded important generalizations and served (...)
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  38.  32
    Analysing Network Models to Make Discoveries About Biological Mechanisms.William Bechtel - 2019 - British Journal for the Philosophy of Science 70 (2):459-484.
    Systems biology provides alternatives to the strategies to developing mechanistic explanations traditionally pursued in cell and molecular biology and much discussed in accounts of mechanistic explanation. Rather than starting by identifying a mechanism for a given phenomenon and decomposing it, systems biologists often start by developing cell-wide networks of detected connections between proteins or genes and construe clusters of highly interactive components as potential mechanisms. Using inference strategies such as ‘guilt-by-association’, researchers advance hypotheses about functions performed of these mechanisms. I (...)
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  39. The Downs and Ups of Mechanistic Research: Circadian Rhythm Research as an Exemplar. [REVIEW]William Bechtel - 2010 - Erkenntnis 73 (3):313 - 328.
    In the context of mechanistic explanation, reductionistic research pursues a decomposition of complex systems into their component parts and operations. Using research on the mechanisms responsible for circadian rhythms, I consider both the gains that have been made by discovering genes and proteins that figure in these intracellular oscillators and also highlight the increasingly recognized need to understand higher-level integration, both between cells in the central oscillator and between the central and peripheral oscillators. This history illustrates a common need to (...)
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  40.  11
    A Companion to Cognitive Science.George Graham & William Bechtel (eds.) - 1998 - Blackwell.
    Part I: The Life of Cognitive Science:. William Bechtel, Adele Abrahamsen, and George Graham. Part II: Areas of Study in Cognitive Science:. 1. Analogy: Dedre Gentner. 2. Animal Cognition: Herbert L. Roitblat. 3. Attention: A.H.C. Van Der Heijden. 4. Brain Mapping: Jennifer Mundale. 5. Cognitive Anthropology: Charles W. Nuckolls. 6. Cognitive and Linguistic Development: Adele Abrahamsen. 7. Conceptual Change: Nancy J. Nersessian. 8. Conceptual Organization: Douglas Medin and Sandra R. Waxman. 9. Consciousness: Owen Flanagan. 10. Decision Making: J. Frank Yates (...)
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  41. Realism, Instrumentalism, and the Intentional Stance.William Bechtel - 1985 - Cognitive Science 9 (4):265-92.
  42. Active Biological Mechanisms: Transforming Energy Into Motion in Molecular Motors.William Bechtel & Andrew Bollhagen - 2021 - Synthese 199 (5-6):12705-12729.
    Unless one embraces activities as foundational, understanding activities in mechanisms requires an account of the means by which entities in biological mechanisms engage in their activities—an account that does not merely explain activities in terms of more basic entities and activities. Recent biological research on molecular motors exemplifies such an account, one that explains activities in terms of free energy and constraints. After describing the characteristic “stepping” activities of these molecules and mapping the stages of those steps onto the stages (...)
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  43.  72
    Why Do Biologists Use so Many Diagrams?Benjamin Sheredos, Daniel Burnston, Adele Abrahamsen & William Bechtel - 2013 - Philosophy of Science 80 (5):931-944.
    Diagrams have distinctive characteristics that make them an effective medium for communicating research findings, but they are even more impressive as tools for scientific reasoning. Focusing on circadian rhythm research in biology to explore these roles, we examine diagrammatic formats that have been devised to identify and illuminate circadian phenomena and to develop and modify mechanistic explanations of these phenomena.
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  44. Constructing a Philosophy of Science of Cognitive Science.William Bechtel - 2009 - Topics in Cognitive Science 1 (3):548-569.
    Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information-processing mechanisms, cognitive science needs an account of (...)
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  45.  48
    Imagining Mechanisms with Diagrams.Benjamin Sheredos & William Bechtel - 2020 - In Arnon Levy & Peter Godfrey-Smith (eds.), The Scientific Imagination: Philosophical and Psychological Perspectives. Oxford University Press.
    Some proponents of mechanistic explanation downplay the significance of how-possibly explanations. We argue that developing accounts of mechanisms that could explain a phenomenon is an important aspect of scientific reasoning, one that involves imagination. Although appeals to imagination may seem to obscure the process of reasoning, we illustrate how, by examining diagrams we can gain insights into the construction of mechanistic explanations.
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  46. Mechanism.Carl Craver & William Bechtel - 2006 - In J. Pfeifer & Sahotra Sarkar (eds.), The Philosophy of Science: An Encyclopedia. Psychology Press. pp. 469--478.
  47. Decomposing, Recomposing, and Situating Circadian Mechanisms: Three Tasks in Developing Mechanistic Explanations.William Bechtel & Adele Abrahamsen - 2009 - In H. Leitgeb & A. Hieke (eds.), Reduction: Between the Mind and the Brain. Ontos. pp. 12--177.
  48.  70
    Design Sans Adaptation.Sara Green, Arnon Levy & William Bechtel - 2015 - European Journal for Philosophy of Science 5 (1):15-29.
    Design thinking in general, and optimality modeling in particular, have traditionally been associated with adaptationism—a research agenda that gives pride of place to natural selection in shaping biological characters. Our goal is to evaluate the role of design thinking in non-evolutionary analyses. Specifically, we focus on research into abstract design principles that underpin the functional organization of extant organisms. Drawing on case studies from engineering-inspired approaches in biology we show how optimality analysis, and other design-related methods, play a specific methodological (...)
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  49. Explanation: Mechanism, Modularity, and Situated Cognition.William Bechtel - 2009 - In Murat Aydede & P. Robbins (eds.), The Cambridge Handbook of Situated Cognition. Cambridge: Cambridge University Press. pp. 155--170.
  50. Reduction, Integration, and the Unity of Science: Natural, Behavioral, and Social Sciences and the Humanities.William P. Bechtel & Andrew Hamilton - 2007 - In T. Kuipers (ed.), Philosophy of Science: Focal Issues (Volume 1 of the Handbook of the Philosophy of Science). Elsevier.
    1. A Historical Look at Unity 2. Field Guide to Modern Concepts of Reduction and Unity 3. Kitcher's Revisionist Account of Unification 4. Critics of Unity 5. Integration Instead of Unity 6. Reduction via Mechanisms 7. Case Studies in Reduction and Unification across the Disciplines.
     
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