Causality and Causal Modelling in the Social Sciences Measuring Variations

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 c...

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Bibliographic Details
Main Author: Russo, Federica
Format: eBook
Language:English
Published: Dordrecht Springer Netherlands 2009, 2009
Edition:1st ed. 2009
Series:Methodos Series, Methodological Prospects in the Social Sciences
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Causality and Causal Modelling in the Social Sciences  |h Elektronische Ressource  |b Measuring Variations  |c by Federica Russo 
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300 |a XIV, 236 p  |b online resource 
505 0 |a 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: Mother’s education and child survival -- 1.4: Health and wealth -- 1.5: Farmer’s 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: Rubin’s model --  
505 0 |a 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 
505 0 |a 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 --  
653 |a Economics 
653 |a Population Economics 
653 |a Population and Demography 
653 |a Sociology / Methodology 
653 |a Philosophy of the Social Sciences 
653 |a Social sciences / Statistical methods 
653 |a Demography 
653 |a Philosophy and social sciences 
653 |a Population 
653 |a Population / Economic aspects 
653 |a Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy 
653 |a Sociological Methods 
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520 |a 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. 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)