The anti-causal prophecies of last century have been disproved. Causality is neither a relic of a bygone nor another fetish of modern science; it still occupies a large part of the current debate in philosophy and the sciences.

This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubin s model, contingency tables, and multilevel analysis. It is also shown to be latent yet fundamental in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability.

This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science.

"Dr. Federica Russo's book is a very valuable addition to a small number of relevant publications on causality and causal modelling in the social sciences viewed from a philosophical approach." (Prof. Guillaume Wunsch, Institute of Demography, University of Louvain, Belgium)"

In scholarly debates, as well as in everyday parlance, we tend to pull science and technology apart: science gives us theory, and technology applies it. In practice, however, science and technologies are highly intertwined. This book sets out to look at the practice of science, and to elucidate the role of technologies and of instruments in the process of knowledge production. In this exercise, it becomes evident that technologies cannot be analyzed on their own, but always in relation to us epistemic agents. Thus, the book pleads for the importance to look at the process of knowledge production in techno-scientific practices, in which there is a triad of relations to look at: us - the instruments - and the world. The book thus builds bridges between Philosophy of Science, Philosophy of Technology, and Science and Technology Studies in an unprecedent way.

In scholarly debates, as well as in everyday parlance, we tend to pull science and technology apart: science gives us theory, and technology applies it. In practice, however, science and technologies are highly intertwined. This book sets out to look at the practice of science, and to elucidate the role of technologies and of instruments in the process of knowledge production. In this exercise, it becomes evident that technologies cannot be analyzed on their own, but always in relation to us epistemic agents. Thus, the book pleads for the importance to look at the process of knowledge production in techno-scientific practices, in which there is a triad of relations to look at: us - the instruments - and the world. The book thus builds bridges between Philosophy of Science, Philosophy of Technology, and Science and Technology Studies in an unprecedent way.

The anti-causal prophecies of last century have been disproved. Causality is neither a relic of a bygone nor another fetish of modern science; it still occupies a large part of the current debate in philosophy and the sciences.

This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubin s model, contingency tables, and multilevel analysis. It is also shown to be latent yet fundamental in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability.

This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science.

"Dr. Federica Russo's book is a very valuable addition to a small number of relevant publications on causality and causal modelling in the social sciences viewed from a philosophical approach." (Prof. Guillaume Wunsch, Institute of Demography, University of Louvain, Belgium)"

This book is open access under a CC BY license. This book is the first to develop explicit methods for evaluating evidence of mechanisms in the field of medicine. It explains why it can be important to make this evidence explicit, and describes how to take such evidence into account in the evidence appraisal process. In addition, it develops procedures for seeking evidence of mechanisms, for evaluating evidence of mechanisms, and for combining this evaluation with evidence of association in order to yield an overall assessment of effectiveness. Evidence-based medicine seeks to achieve improved health outcomes by making evidence explicit and by developing explicit methods for evaluating it. To date, evidence-based medicine has largely focused on evidence of association produced by clinical studies. As such, it has tended to overlook evidence of pathophysiological mechanisms and evidence of the mechanisms of action of interventions. The book offers a useful guide for all those whose work involves evaluating evidence in the health sciences, including those who need to determine the effectiveness of health interventions and those who need to ascertain the effects of environmental exposures.

Head hits cause brain damage - but not always. Should we ban sport to protect athletes? Exposure to electromagnetic fields is strongly associated with cancer development - does that mean exposure causes cancer? Should we encourage old fashioned communication instead of mobile phones to reduce cancer rates? According to popular wisdom, the Mediterranean diet keeps you healthy. Is this belief scientifically sound? Should public health bodies encourage consumption of fresh fruit and vegetables? Severe financial constraints on research and public policy, media pressure, and public anxiety make such questions of immense current concern not just to philosophers but to scientists, governments, public bodies, and the general public. In the last decade there has been an explosion of theorizing about causality in philosophy, and also in the sciences. This literature is both fascinating and important, but it is involved and highly technical. This makes it inaccessible to many who would like to use it, philosophers and scientists alike. This book is an introduction to philosophy of causality - one that is highly accessible: to scientists unacquainted with philosophy, to philosophers unacquainted with science, and to anyone else lost in the labyrinth of philosophical theories of causality. It presents key philosophical accounts, concepts and methods, using examples from the sciences to show how to apply philosophical debates to scientific problems.

There is a need for integrated thinking about causality, probability and mechanisms in scientific methodology. Causality and probability are long-established central concepts in the sciences, with a corresponding philosophical literature examining their problems. On the other hand, the philosophical literature examining mechanisms is not long-established, and there is no clear idea of how mechanisms relate to causality and probability. But we need some idea if we are to understand causal inference in the sciences: a panoply of disciplines, ranging from epidemiology to biology, from econometrics to physics, routinely make use of probability, statistics, theory and mechanisms to infer causal relationships.
These disciplines have developed very different methods, where causality and probability often seem to have different understandings, and where the mechanisms involved often look very different. This variegated situation raises the question of whether the different sciences are really using different concepts, or whether progress in understanding the tools of causal inference in some sciences can lead to progress in other sciences. The book tackles these questions as well as others concerning the use of causality in the sciences.

An accessible guide for those facing the study of Logic for the first time, this book covers key thinkers, terms and texts. "The Key Terms in Philosophy" series offers clear, concise and accessible introductions to the central topics in philosophy. Each book offers a comprehensive overview of the key terms, concepts, thinkers and major works in the history of a key area of philosophy. Ideal for first-year students starting out in philosophy, the series will serve as the ideal companion to study of this fascinating subject. "Key Terms in Logic" offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no prior knowledge of the subject, this is the ideal reference tool for those coming to Logic for the first time. "The Key Terms" series offers undergraduate students clear, concise and accessible introductions to core topics. Each book includes a comprehensive overview of the key terms, concepts, thinkers and texts in the area covered and ends with a guide to further resources.

Causal inference is perhaps the most important form of reasoning in the sciences. A panoply of disciplines, ranging from epidemiology to biology, from econometrics to physics, make use of probability and statistics in order to infer causal relationships. However, the very foundations of causal inference are up in the air; it is by no means clear which methods of causal inference should be used, nor why they work when they do. This book brings philosophers and scientists together to tackle these important questions. The papers in this volume shed light on the relationship between causality and probability and the application of these concepts within the sciences. With its interdisciplinary perspective and its careful analysis, "Causality and Probability in the Sciences" heralds the transition of causal inference from an art to a science.

This is an accessible guide for those facing the study of Logic for the first time, this book covers key thinkers, terms and texts. "The Key Terms in Philosophy" series offers clear, concise and accessible introductions to the central topics in philosophy. Each book offers a comprehensive overview of the key terms, concepts, thinkers and major works in the history of a key area of philosophy. Ideal for first-year students starting out in philosophy, the series will serve as the ideal companion to study of this fascinating subject. "Key Terms in Logic" offers the ideal introduction to this core area in the study of philosophy, providing detailed summaries of the important concepts in the study of logic and the application of logic to the rest of philosophy. A brief introduction provides context and background, while the following chapters offer detailed definitions of key terms and concepts, introductions to the work of key thinkers and lists of key texts. Designed specifically to meet the needs of students and assuming no prior knowledge of the subject, this is the ideal reference tool for those coming to Logic for the first time. "The Key Terms" series offers undergraduate students clear, concise and accessible introductions to core topics. Each book includes a comprehensive overview of the key terms, concepts, thinkers and texts in the area covered and ends with a guide to further resources.