Striving to boldly redirect the philosophy of science, this book by renowned philosopher Philip Kitcher examines the heated debate surrounding the role of science in shaping our lives. Kitcher explores the sharp divide between those who believe that the pursuit of scientific knowledge is always valuable and necessary--the purists--and those who believe that it invariably serves the interests of people in positions of power. In a daring turn, he rejects both perspectives, working out a more realistic image of the sciences--one (...) that allows for the possibility of scientific truth, but nonetheless permits social consensus to determine which avenues to investigate. He then proposes a democratic and deliberative framework for responsible scientists to follow. Controversial, powerful, yet engaging, this volume will appeal to a wide range of readers. Kitcher's nuanced analysis and authorititative conclusion will interest countless scientists as well as all readers of science--scholars and laypersons alike. (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)

Following Dretske (1977), there has been a considerable body of literature on the role of contrastive stress in causal claims. Following van Fraassen (1980), there has been a considerable body of literature on the role of contrastive stress in explanations and explanation-requesting why-questions. Amazingly, the two bodies of literature have remained almost entirely disjoint. With an understanding of the contrastive nature of ordinary causal claims, and of the linguistic roles of contrastive stress, it is possible to provide a unified account (...) of both phenomena. I provide such an account from within the framework of a probabilistic theory of causation. Relations of screening-off, long familiar to researchers in probabilistic causality, play a central role in this account. (shrink)

This paper discusses several distinct process theories of causality offered in recent years by Phil Dowe and me. It addresses problems concerning the explication of causal process, causal interaction, and causal transmission, whether given in terms of transmission of marks, transmission of invariant or conserved quantities, or mere possession of conserved quantities. Renouncing the mark-transmission and invariant quantity criteria, I accept a conserved quantity theory similar to Dowe's--differing basically with respect to causal transmission. This paper also responds to several fundamental (...) constructive criticisms contained in Christopher Hitchcock's discussion of both the mark-transmission and the conserved quantity theories. (shrink)

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws (...) can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization. (shrink)

"Theoretical pluralism" obtains when there are good evidential reasons for accommodating multiple theories of the same domain. Issues of "relative significance" often arise in connection with the investigation of such domains. In this paper, I describe and give examples of theoretical pluralism and relative significance issues. Then I explain why theoretical pluralism so often obtains in biology--and why issues of relative significance arise--in terms of evolutionary contingencies and the paucity or lack of laws of biology. Finally, I turn from explanation (...) to justification, and raise questions about the purpose and value of concerns and disagreements about relative significance. (shrink)

This paper offers an account of what it is for a physical system to be a computing mechanism—a system that performs computations. A computing mechanism is a mechanism whose function is to generate output strings from input strings and (possibly) internal states, in accordance with a general rule that applies to all relevant strings and depends on the input strings and (possibly) internal states for its application. This account is motivated by reasons endogenous to the philosophy of computing, namely, doing (...) justice to the practices of computer scientists and computability theorists. It is also an application of recent literature on mechanisms, because it assimilates computational explanation to mechanistic explanation. The account can be used to individuate computing mechanisms and the functions they compute and to taxonomize computing mechanisms based on their computing power. (shrink)

Carl F. Craver investigates what we are doing when we use neuroscience to explain what's going on in the brain. When does an explanation succeed and when does it fail? Craver offers explicit standards for successful explanation of the workings of the brain, on the basis of a systematic view about what neuroscientific explanations are.

During the scientific revolution reductionism and mechanism were introduced together. These concepts remained intertwined through much of the ensuing history of philosophy and science, resulting in the privileging of approaches to research that focus on the smallest bits of nature. This combination of concepts has been the object of intense feminist criticism, as it encourages biological determinism, narrows researchers’ choices of problems and methods, and allows researchers to ignore the contextual features of the phenomena they investigate. I argue that the (...) historical link between mechanism and reductionism is not a necessary one, that this link should be severed, and in many cases has already been severed. Teasing reductionism away from mechanism allows us to hold onto the mechanistic view that science should explain how things work, without mandating methods and approaches that reduce the objects of scientific investigation to their smallest parts. Mechanism without reductionism decenters reductive methods, and so creates intellectual space for a plurality of methods that may engage the world at a variety of levels of organization. This ensuing pluralism opens the door for a wide variety of approaches to research, including feminist and gender-sensitive science. (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)

mechanism" is frequently encountered in the social science literature, but there is considerable confusion about the exact meaning of the term. The article begins by addressing the main conceptual issues. Use of this term is the hallmark of an approach that is critical of the explanatory deficits of correlational analysis and of the covering-law model, advocating instead the causal reconstruction of the processes that account for given macro-phenomena. The term "social mechanisms" should be used to refer to recurrent processes generating (...) a specific kind of outcome. Explanation of social macro-phenomena by mechanisms typically involves causal regression to lower-level elements, as stipulated by methodological individualism. While there exist a good many mechanism models to explain emergent effects of collective behavior, we lack a similarly systematic treatment of generative mechanisms in which institutions and specific kinds of structural configurations play the decisive role. Key Words: causal regression • correlational analysis • emergent effects • micro-macro processes • social mechanisms • structural determinants. (shrink)

This article examines the role of experimental generalizations and physical laws in neuroscientific explanations, using Hodgkin and Huxley’s electrophysiological model from 1952 as a test case. I show that the fact that the model was partly fitted to experimental data did not affect its explanatory status, nor did the false mechanistic assumptions made by Hodgkin and Huxley. The model satisfies two important criteria of explanatory status: it contains invariant generalizations and it is modular (both in James Woodward’s sense). Further, I (...) argue that there is a sense in which the explanatory heteronomy thesis holds true for this case. †To contact the author, please write to: SNF‐Professorship for Philosophy of Science, University of Basel, Missionsstrasse 21, 4003 Basel, Switzerland; e‐mail: [email protected]. (shrink)

A biochemical pathway is a sequence of chemical reactions in a biological organism. Such pathways specify mechanisms that explain how cells carry out their major functions by means of molecules and reactions that produce regular changes. Many diseases can be explained by defects in pathways, and new treatments often involve finding drugs that correct those defects. This paper presents explanation schemas and treatment strategies that characterize how thinking about pathways contributes to biomedical discovery. It discusses the significance of pathways for (...) understanding the nature of diseases, explanations, and theories. (shrink)

The claim that a functional kind is multiply realized is typically motivated by appeal to intuitive examples. We are seldom told explicitly what the relevant structures are, and people have often preferred to rely on general intuitions in these cases. This article deals with the problem by explaining how to understand the proper relation between structural kinds and the functions they realize. I will suggest that the structural kinds that realize a function can be properly identified by attending to the (...) context of functional explanation. *Received June 2006; revised June 2009. †To contact the author, please write to: Department of Philosophy, Seton Hall University, 400 South Orange Ave., South Orange, NJ 07079; e‐mail: [email protected]. (shrink)

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)

The orthodox, empiricist covering-law account of scientific explanation, as developed by C. G. Hempel and others, has long dominated philosophical discussions of scientific explanation. In recent years it has met overwhelming critical resistance. We should give up this account of scientific ex.