Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

“What is an emotion?” William James asked that question in the title of an essay he wrote in 1884, and his answer was that an emotion is a sensation brought about by bodily disturbance. Writing as a psychologist, he was concerned to help turn his discipline into a science. But as a philosopher writing about religious faith, by contrast, James argued that emotions must be understood in terms of such large and fuzzy issues as “the meaning of life.” The philosophy (...) of emotions and emotions research has since gone off in two quite different directions, one a broad-based perennial philosophical concern with the proper place of the emotions in ethics and living well, the other an increasingly sophisticated pursuit of the latest ammunition and theoretical weaponry in the biological and neurological sciences. (shrink)

The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust (...) argument for scientific realism akin to the argument that convinced twentieth-century physical scientists of the existence of atoms and molecules. To do justice to such notions as irreducibly statistical laws and statistical explanation, he offers a novel account of physical randomness. The transition from the "reviewed view" of scientific explanation to the causal/mechanical model requires fundamental rethinking of basic explanatory concepts. (shrink)

According to Philip Kitcher, scientific unification is achieved via the derivation of numerous scientific statements from economies of argument schemata. I demonstrate that the unification of selection phenomena across domains in which it is claimed to occur--evolutionary biology, immunology and, speculatively, neurobiology--is unattainable on Kitcher's view. I then introduce an alternative method for rendering the desired unification based on the concept of a mechanism schema. I conclude that the gain in unification provided by the alternative account suggests that Kitcher's view (...) is defective. (shrink)

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.

expose some gaps and difficulties in the argument for the causal Markov condition in our essay ‘Independence, Invariance and the Causal Markov Condition’ ([1999]), and we are grateful for the opportunity to reformulate our position. In particular, Cartwright disagrees vigorously with many of the theses we advance about the connection between causation and manipulation. Although we are not persuaded by some of her criticisms, we shall confine ourselves to showing how our central argument can be reconstructed and to casting doubt (...) on Cartwright's claim that the causal Markov condition typically fails when there are indeterministic by-products. Why believe the causal Markov condition? Causation and manipulation The argument Indeterministic by-products and the causal Markov condition The chemical factory counterexample and PM2 Conclusions: causation and manipulability. (shrink)

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 certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

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 certain (...) objections to Salmon's account of causal-mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

In this paper I offer an analysis of causation based upon a theory of mechanisms-complex systems whose internal parts interact to produce a system's external behavior. I argue that all but the fundamental laws of physics can be explained by reference to mechanisms. Mechanisms provide an epistemologically unproblematic way to explain the necessity which is often taken to distinguish laws from other generalizations. This account of necessity leads to a theory of causation according to which events are causally related when (...) there is a mechanism that connects them. I present reasons why the lack of an account of fundamental physical causation does not undermine the mechanical account. (shrink)

With this manifesto, John Dupré systematically attacks the ideal of scientific unity by showing how its underlying assumptions are at odds with the central conclusions of science itself.

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 certain (...) objections to Salmon’s account of causal‐mechanical explanation. I conclude by discussing how mechanistic explanations can provide understanding by unification. (shrink)

SummaryThis paper addresses the question of what scientific realism implies and what it does not when it is articulated so as to provide the best defense against plausible philosophical alternatives. A summary is presented of “abductive” arguments for scientific realism, and of the epistemological and semantic conceptions upon which they depend. Taking these arguments to be the best current defense of realism, it is inquired what, in the sense just mentioned, realism implies and what it does not. It is concluded (...) that realism implies the strong rejection of epistemological foundationalism, a non‐Humean conception of causation and of explanation, and a causal rather than conceptual account of the unity of natural definitions. It is denied that realism implies bivalence or the existence of one true theory, one preferred vocabulary or one distinctly privileged science. It is further denied that realism implies that there are no unrecognized conventional aspects to scientific theorizing and it is denied that realism implies that scientists routinely do good experimental metaphysics. (shrink)

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 (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

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 (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

Assembled by the prominent psychologists Daniel Schacter and Endel Tulving, the contributions in Memory Systems 1994 focus on the nature and number of memory systems in humans and animals. Together they present ideas from cognitive psychology, neuropsychology, and neuroscience in a review of intriguing experimental outcomes at the cutting edge of this domain, grappling, often passionately, with the behavioral and neuroanatomical composition of memory systems and subsystems. Chapters are revised versions of contributions that appeared in a special issue of the (...) Journal of Cognitive Neuroscience. This book includes an integrated discussion of and cross-commentary on the earlier contributions. (shrink)

This study synthesizes current information from the various fields of cognitive science in support of a new and exciting theory of mind. Most psychologists study horizontal processes like memory and information flow; Fodor postulates a vertical and modular psychological organization underlying biologically coherent behaviors. This view of mental architecture is consistent with the historical tradition of faculty psychology while integrating a computational approach to mental processes. One of the most notable aspects of Fodor's work is that it articulates features not (...) only of speculative cognitive architectures but also of current research in artificial intelligence. (shrink)

This collection of original essays--by philosophers of biology, biologists, and cognitive scientists--provides a wide range of perspectives on species. Including contributions from David Hull, John Dupre, David Nanney, Kevin de Queiroz, and Kim Sterelny, amongst others, this book has become especially well-known for the three essays it contains on the homeostatic property cluster view of natural kinds, papers by Richard Boyd, Paul Griffiths, and Robert A. Wilson.

A provocative assessment of human thought and behavior, reissued with a new afterword, explores a range of conundrums from the ability of the mind to perceive three dimensions to the nature of consciousness, in an account that draws on ...

Paul E. Griffiths argues that most research on the emotions has been as misguided as Aristotelian efforts to study "superlunary objects" - objects...

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.