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In Making Things Happen, James Woodward develops a new and ambitious comprehensive theory of causation and explanation that draws on literature from a variety of disciplines and which applies to a wide variety of claims in science and everyday life. His theory is a manipulationist account, proposing that causal and explanatory relationships are relationships that are potentially exploitable for purposes of manipulation and control. This account has its roots in the commonsense idea that causes are means for bringing about effects; but it also draws on a long tradition of work in experimental design, econometrics, and statistics. Woodward shows how these ideas may be generalized to other areas of science from the social scientific and biomedical contexts for which they were originally designed. He also provides philosophical foundations for the manipulationist approach, drawing out its implications, comparing it with alternative approaches, and defending it from common criticisms. In doing so, he shows how the manipulationist account both illuminates important features of successful causal explanation in the natural and social sciences, and avoids the counterexamples and difficulties that infect alternative approaches, from the deductive-nomological model onwards. Making Things Happen will interest philosophers working in the philosophy of science, the philosophy of social science, and metaphysics, and as well as anyone interested in causation, explanation, and scientific methodology.
This book draws on advances in computational neuroscience and theoretical biology to provide a clear and accessible agentive account of the nature of causality and scientific explanations. Instead of attempting to establish the elements of scientific explanation, such as causality, in a reality unadulterated by a human perspective, this book relies on scientific facts about cognition to describe the structure of agency from a distinctly human perspective. The book draws on the Free Energy Principle to reinforce the agency theory of causality and extend it to an account of explanation as well. This principle not only provides a theoretical account of how self-organising systems engage with the causal structure of the environment, but it also offers a viable notion of agency and is compatible with the projectivist aspects of the agency theory. Scientific Explanation, Causality, and Agency will appeal to researchers and advanced students working in philosophy of science, philosophy of cognitive science, epistemology, computational neuroscience, and theoretical biology.
There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.
A comprehensive examination of methods for mediation and interaction, VanderWeele's book is the first to approach this topic from the perspective of causal inference. Numerous software tools are provided, and the text is both accessible and easy to read, with examples drawn from diverse fields. The result is an essential reference for anyone conducting empirical research in the biomedical or social sciences.
This book, published in 2000, discusses in a systematic way, a positive account of causation.
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.
Research design is of critical importance in social research, despite its relative neglect in many methods resources. Early consideration of design in relation to research questions leads to the elimination or diminution of threats to eventual research claims, by encouraging internal validity and substantially reducing the number of alternative explanations for any finite number of research ′observations′. This new book: discusses the nature of design; gives an introduction to design notation; offers a flexible approach to new designs; looks at a range of standard design models; and presents craft tips for real-life problems and compromises. Most importantly, it provides the rationale for preferring one design over another within any given context. Each section is illustrated with case studies of real work and concludes with suggested readings and topics for discussion in seminars and workshops, making it an ideal textbook for postgraduate research methods courses. Based on the author′s teaching on the ESRC Doctoral Training Centre "Masters in Research Methods" at the University of Birmingham, and his ongoing work for the ESRC Researcher Development Initiative, this is an essential text for postgraduate researchers and academics. There is no book like Research Design on the market that addresses all of these issues in an easy to comprehend style, for those who want to design research and make critical judgements about the designs of others.
A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
This innovative research design text will help you make informed choices when carrying out your research project. Covering both qualitative and quantitative approaches, and with examples drawn from a wide range of social science disciplines, the authors explain what is at stake when choosing a research design, and discuss the trade-offs that researchers have to make when considering issues such as: - causality - categories and classification - heterogeneity - interdependence - time This book will appeal to students and researchers looking for an in-depth understanding of research design issues to help them design their projects in a thoughtful and responsible way.
Not all scientific explanations work by describing causal connections between events or the world's overall causal structure. In addition, mathematicians regard some proofs as explaining why the theorems being proved do in fact hold. This book proposes new philosophical accounts of many kinds of non-causal explanations in science and mathematics.