This book, published in 2000, is a clear account of causation based firmly in contemporary science. Dowe discusses in a systematic way, a positive account of causation: the conserved quantities account of causal processes which he has been developing over the last ten years. The book describes causal processes and interactions in terms of conserved quantities: a causal process is the worldline of an object which possesses a conserved quantity, and a causal interaction involves the exchange of conserved quantities. Further, (...) things that are properly called cause and effect are appropriately connected by a set of causal processes and interactions. The distinction between cause and effect is explained in terms of a version of the fork theory: the direction of a certain kind of ordered pattern of events in the world. This particular version has the virtue that it allows for the possibility of backwards causation, and therefore time travel. (shrink)

Hunting Causes and Using Them argues that causation is not one thing, as commonly assumed, but many. There is a huge variety of causal relations, each with different characterizing features, different methods for discovery and different uses to which it can be put. In this collection of new and previously published essays, Nancy Cartwright provides a critical survey of philosophical and economic literature on causality, with a special focus on the currently fashionable Bayes-nets and invariance methods - and it exposes (...) a huge gap in that literature. Almost every account treats either exclusively how to hunt causes or how to use them. But where is the bridge between? It's no good knowing how to warrant a causal claim if we don't know what we can do with that claim once we have it. This book will interest philosophers, economists and social scientists. (shrink)

Understanding Scientific Reasoning, Fifth Edition, develops critical reasoning skills and guides students in the improvement of their scientific and technological literacy. The authors teach students how to understand and critically evaluate the scientific information they encounter in both textbooks and the popular media. With its focus on scientific pedagogy, Understanding Scientific Reasoning helps students learn how to examine scientific reports with a reasonable degree of sophistication. The book also explains how to reason through case studies using the same informal logic (...) skills employed by scientists and to analyse a complex series of propositions and hypotheses using sound scientific reasoning--Publisher's blurb. (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.

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)

Thirty years after Lewis's paper, this book brings together some of the most important recent work connecting—or, in some cases, disputing the connection ...

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.

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

The paper has two aims. First, to show that we need social mechanisms to establish the policy relevance of causal claims, even if it is possible to build a good argument for those claims without knowledge of mechanisms. Second, to show that although social scientists can, in principle, do without social mechanisms when they argue for causal claims, in reality scientific practice contexts where they do not need mechanisms are very rare. Key Words: social mechanisms • causal inference • social (...) policy. (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)

We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

La autora presenta algunas criticas generales al proyecto de reducir las leyes causales a probabilidades. Además, muestra que las leyes causales son imprescindibles para poder diferenciar las strategias efectivas de las que no lo son y da un criterio para considerar cuando podemos deducir causalidad a través de datos estadísticos.

This book provides a post-positivist theory of deterministic and probabilistic causality that supports both quantitative and qualitative explanations. Features of particular interest include the ability to provide true explanations in contexts where our knowledge is incomplete, a systematic interpretation of causal modeling techniques in the social sciences, and a direct realist view of causal relations that is compatible with a liberal empiricism. The book should be of wide interest to both philosophers and scientists. Originally published in 1989. The Princeton Legacy (...) Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905. (shrink)

Epidemiologists’ discussions on causation are not always very enlightening with regard to the notion of ‘cause’ in epidemiology. Epidemiologists rightly work from a science-based approach to causation in epidemiology, but largely disagree about the matter. Disagreement may be partly due to confusion of the question of useful concepts for causal inference in epidemiological practice with the question of the metaphysical presuppositions of causal concepts used in epidemiology. In other words, epidemiologists seem to confuse the practical results of epidemiological research at (...) the population level with the metaphysical views about the reality of disease causation at the individual level in their writings on causation. (shrink)

Professor Little presents an introduction to the philosophy of social science with an emphasis on the central forms of explanation in social science: rational-intentional, causal, functional, structural, materialist, statistical and interpretive. The book is very strong on recent developments, particularly in its treatment of rational choice theory, microfoundations for social explanation, the idea of supervenience, functionalism, and current discussions of relativism.Of special interest is Professor Little’s insight that, like the philosophy of natural science, the philosophy of social science can profit (...) from examining actual scientific examples. Throughout the book, philosophical theory is integrated with recent empirical work on both agrarian and industrial society drawn from political science, sociology, geography, anthropology, and economics.Clearly written and well structured, this text provides the logical and conceptual tools necessary for dealing with the debates at the cutting edge of contemporary philosophy of social science. It will prove indispensible for philosophers, social scientists and their students. (shrink)

Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interpreted in a way that does not depend on it. Nevertheless, he shows that this more charitable version of the account is (...) still unsuccessful as it stands. Consequently, he advances a proposal for shoring up the account, which is founded on the possibility of acquiring knowledge of social mechanisms by linking together norms or practices found in a society. Key Words: causality • social mechanisms • interpretation • anthropology. (shrink)

This book, by one of the pre-eminent philosophers of science writing today, offers the most comprehensive account available of causal asymmetries. Causation is asymmetrical in many different ways. Causes precede effects; explanations cite causes not effects. Agents use causes to manipulate their effects; they don't use effects to manipulate their causes. Effects of a common cause are correlated; causes of a common effect are not. This book explains why a relationship that is asymmetrical in one of these regards is asymmetrical (...) in the others. Hausman discovers surprising hidden connections between theories of causation and traces them all to an asymmetry of independence. This is a major book for philosophers of science that will also prove insightful to economists and statisticians. (shrink)

In this important book, Ellery Eells explores and refines philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified. Philosophical interest in this subject arises from attempts to understand population sciences as well as indeterminism in physics. Taking into account issues involving spurious correlation, probabilistic causal interaction, disjunctive causal factors, and temporal ideas, Professor Eells advances the analysis of what (...) it is for one factor to be a positive causal factor for another. A salient feature of the book is a theory of token level probabilistic causation in which the evolution of the probability of a later event from an earlier event is central. This will be a book of crucial significance to philosophers of science and metaphysicians; it will also prove stimulating to many economists, psychologists, and physicists. (shrink)

In the past 25 years, many philosophers have endorsed the view that the practical value of causal knowledge lies in the fact that manipulation of causes is a good way to bring about a desired change in the effect. This view is intuitively very plausible. For instance, we can predict a storm on the basis of a barometer reading, but we cannot avoid the storm by manipulating the state of the barometer (barometer status and storm are effects of a common (...) cause, viz. atmospheric conditions). In §1 we present textual evidence which shows that this view is very popular. In §2 we show that this standard view is too restrictive: the practical value of causal knowledge is wider. In §3 we introduce the distinction between ‘manipulative policy’ and ‘selective policy’ as a theoretical framework to account for this wider practical value. (shrink)

In what follows, I propose to evaluate Giere's analysis by applying it to a causal process considered in evolutionary theory, namely, natural selection. To say that there is selection for a given trait is to say that possessing that trait causes differential reproductive success. If there is selection for a trait and if no other evolutionary forces impinge and there is no "sampling error" due to random drift, individuals with the trait will on average have more offspring than individuals without (...) it. But sampling error can't be discounted for finite populations; so the combined effect of selection and drift will be a probability distribution of numbers of offspring. In this event, selection for a trait will imply that the mean value of the distribution associated with the individuals possessing the trait exceeds the mean value for individuals without the trait. Evolutionary theory assigns a probability distribution of possible reproductive outputs to each organism and, thereby, views organisms as stochastic systems. This implies no commitment to indeterminacy at the microlevel, of course. (shrink)

Inferences like these are known as extrapolations.

The purpose of this essay is to investigate the properties of singular causal systems and their population manifestations, with special concern for the thesis of methodological individualism, which claims that there are no properties of social groups that cannot be adequately explained exclusively by reference to properties of individual members of those groups, i.e., at the level of individuals. Individuals, however, may be viewed as singular causal systems, i.e., as instantiations of (arrangements of) dispositional properties. From this perspective, methodological individualism (...) appears to be an ambiguous thesis: some properties of collections of (independent) systems of the same kind are reducible, but other properties of collections of (dependent) systems of the same kind are not. In cases of the first kind, therefore, methodological individualism is true, but trivial; while in cases of the second kind, it is significant, but false. Hence, if the arguments that follow are correct, at least some of the properties of social groups should qualify as emergent. (shrink)

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, defences, objections, and replies into a convincing defence of the core of his theory, which is that we can analyse causation by appeal to the notion of manipulation.

Epidemiologists’ discussions on causation are not always very enlightening with regard to the notion of ‘cause’ in epidemiology. Epidemiologists rightly work from a science-based approach to causation in epidemiology, but largely disagree about the matter. Disagreement may be partly due to confusion of the question of useful concepts for causal inference in epidemiological practice with the question of the metaphysical presuppositions of causal concepts used in epidemiology. In other words, epidemiologists seem to confuse the practical results of epidemiological research at (...) the population level with the metaphysical views about the reality of disease causation at the individual level in their writings on causation. (shrink)

In the past 25 years, many philosophers have endorsed the view that the practical value of causal knowledge lies in the fact that manipulation of causes is a good way to bring about a desired change in the effect. This view is intuitively very plausible. For instance, we can predict a storm on the basis of a barometer reading, but we cannot avoid the storm by manipulating the state of the barometer (barometer status and storm are effects of a common (...) cause, viz. atmospheric conditions). In Section 1 we present textual evidence which shows that this view is very popular. In Section 2 we show that this standard view is too restrictive: the practical value of causal knowledge is wider. In Section 3 we introduce the distinction between ‘manipulative policy’ and ‘selective policy’ as a theoretical framework to account for this wider practical value. (shrink)

Time and cause present apparent asymmetries. What happens later depends on what happens earlier, and not the other way around. Effects depend on their causes, and not the other way around.

The International Agency for Research on Cancer (IARC) is an organization which seeks to identify the causes of human cancer. Per agent, such as betel quid or Human Papillomaviruses, they review the available evidence deriving from epidemiological studies, animal experiments and information about mechanisms (and other data). The evidence of the different groups is combined such that an overall assessment of the carcinogenicity of the agent in question is obtained. In this paper, we critically review the IARC’s carcinogenicity evaluations. First (...) we show that serious objections can be raised against their criteria and procedures – more specifically regarding the role of mechanistic knowledge in establishing causal claims. Our arguments are based on the problem of confounders, of the assessment of the temporal stability of carcinogenic relations, and of the extrapolation from animal experiments. Then we address a very important question, viz. how we should treat the carcinogenicity evaluations that were based on the current procedures. After showing that this question is important, we argue that an overall dismissal of the current evaluations would be too radical. Instead, we argue in favour of a stepwise re-evaluation of the current findings. (shrink)