Causality and Causal Modelling in the Social Sciences: Measuring Variations by F

Description: Causality and Causal Modelling in the Social Sciences by Federica Russo This investigation into causal modelling presents the rationale of causality; i.e. what guides reasoning in causal modeling. In contrast to the dominant paradigm, it argues that causal models are governed by a variation, rather than regularity or invariance. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description 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. Rubins 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 Russos 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) Back Cover 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, not of regularity nor invariance, thus breaking down the dominant Humean paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubins 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 Russos 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) Table of Contents Preface.- Introduction.- 1: Scope of the book and methodology.- 2: Structure of the book.- 3: Philosophical issue in the back of the mind.- 4: Philosophy at the service of social research.- 5: Open problems: causal realism, objectivity, and social ontology.- 1: What do social scientists do?- Introduction.- 1.1: Different causal claims?- 1.2: Smoking and lung cancer.- 1.3: Mothers education and child survival.- 1.4: Health and wealth.- 1.5: Farmers migration.- 1.6: Job satisfaction.- 1.7: Methodological and epistemological morals.- 2: Probabilistic approaches.- Introduction.- 2.1: Philosophical accounts: Good and Suppes.- 2.2: probabilistic theories: traditional criticisms.- 2.3: Brining causal theory to maturity.- 3: Methodology of causal modeling.- Introduction.- 3.1: Methods and assumptions of causal modeling.- 3.1.1: Path models and causal diagrams.- 3.1.2: Covariance structure models.- 3.1.3: Granger-causality.- 3.1.4: Rubins model.- 3.1.5: Multilevel analysis.- 3.1.6: Contingency tables.- 3.2: Hypothetico-deductive methodology.- 3.3: Difficulties and weaknesses of causal modeling.- 4: Epistemology of causal modeling.- Introduction.- 4.1: The rationale of causality: Measuring variations.- 4.2: Varieties of variations.- 4.3: Wha guarantees the causal interpretation?- 4.3.1: Associational models.- 4.3.2: Causal models.- 5: Methodological consequences: objective Bayesianism.- Introduction.- 5.1: Probabilistic causal inferences.- 5.2: Interpretations of probability.- 5.3: The case for frequency-driven epistemic probabilities.- 6: Methodological consequences: mechanisms and levels of causation.- Introduction.- 6.1: Mechanisms.- 6.1.1" Modelling mechanisms.- 6.1.2: Mixed mechanisms.- 6.1.3 Explaining through mechanisms.- 6.1.4: Modelling causal mechanisms vs. modeling decision-making processes.- 6.2: Levels of causation.- 6.2.1: Twofold causality.- 6.3: Levels of analysis.- 6.3.1: Types of variables and of fallacies.- 6.3.2: Levels of analysis vs. levelsof causation.- 6.3.3: Levels of analysis.- 6.3.4: Levels of analysis and variation in multilevel models.- 7: Supporting the rationale of variations.- Introduction,- 7.1: Variation in mechanist approaches.- 7.2: Variation in counterfactuals.- 7.3: Variation in agency theories.- 7.4: Variation in manipulability theories.- 7.5: Variation in epistemic causality.- 7.6: Variation in single instances: concluding remarks.- 1: Objectives, methodology, and results.- 2: The methodological import of philosophical results.- References.- Index. Review From the reviews:"Few books in philosophy specifically deal with causality in the social sciences. Fewer still draw on real examples taken from the social science literature. Here is an exception to the rule. Though a philosopher, Dr. Russo has an extensive background in the social sciences and has collaborated with social scientists in several of her research projects.Causality and Causal Modelling in the Social Sciences: Measuring Variations is therefore a compulsory reading both for philosophers of science and for social scientists. For philosophers on the one hand, reading this book is a good way of experiencing how social science is actually done, far from the arm-chair view of scientific practice. For social scientists on the other hand, it is a way of confronting their practice in causal research to broader concerns in the philosophy of science. Strongly recommended also to the sceptics who believe that, because there are no general laws in the social sphere, causal explanations are impossible. They will think twice after reading this book."(Prof. Guillaume Wunsch, Institute of Demography, University of Louvain, Belgium)"In Causality and Causal Modelling in the Social Sciences, Federica Russo attempts a mutually enlightening exchange between the philosophical literature on causation and causal modeling approaches in social science. … The coverage of the philosophical literature on causation is good … . does a good job of providing an overview of current philosophical discussions of causation and probability, and I think it should be commended for attempting to systematically engage this philosophical literature with real social science research." (Daniel Steel, British Journal for the Philosophy of Science, Vol. 63 (3), September, 2012) Long Description 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. Rubins 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 Russos 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) Review Quote From the reviews:"Few books in philosophy specifically deal with causality in the social sciences. Fewer still draw on real examples taken from the social science literature. Here is an exception to the rule. Though a philosopher, Dr. Russo has an extensive background in the social sciences and has collaborated with social scientists in several of her research projects.Causality and Causal Modelling in the Social Sciences: Measuring Variations is therefore a compulsory reading both for philosophers of science and for social scientists. For philosophers on the one hand, reading this book is a good way of experiencing how social science is actually done, far from the arm-chair view of scientific practice. For social scientists on the other hand, it is a way of confronting their practice in causal research to broader concerns in the philosophy of science. Strongly recommended also to the sceptics who believe that, because there are no general laws in the social sphere, causal explanations are impossible. They will think twice after reading this book."(Prof. Guillaume Wunsch, Institute of Demography, University of Louvain, Belgium)In Causality and Causal Modelling in the Social Sciences, Federica Russo attempts a mutually enlightening exchange between the philosophical literature on causation and causal modeling approaches in social science. … The coverage of the philosophical literature on causation is good … . does a good job of providing an overview of current philosophical discussions of causation and probability, and I think it should be commended for attempting to systematically engage this philosophical literature with real social science research. (Daniel Steel, British Journal for the Philosophy of Science, Vol. 63 (3), September, 2012) Feature The first book to focus on the notion of variation in causal reasoning Includes an accessible overview of the methodology of causal modelling Provides a thorough discussion of philosophical accounts of causality Bridges the gap between philosophy and the social sciences Presents a defence of objective Bayesianism in causal modelling Details ISBN9048179963 Author Federica Russo Publisher Springer Series Methodos Series Year 2010 ISBN-10 9048179963 ISBN-13 9789048179961 Format Paperback Publication Date 2010-11-18 Imprint Springer Place of Publication Dordrecht Country of Publication Netherlands DEWEY 300.1 Edition 1st Short Title CAUSALITY & CAUSAL MODELLING I Language English Media Book Series Number 5 Subtitle Measuring Variations Pages 236 Illustrations XIV, 236 p. Edition Description Softcover reprint of hardcover 1st ed. 2009 Alternative 9781402088162 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96288842;

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