Causation
Book information
Description
This Element provides an accessible introduction to the contemporary philosophy of causation. It introduces the reader to central concepts and distinctions (type vs token causation, probabilistic vs deterministic causation, difference-making, interventions, overdetermination, pre-emption) and to key tools (structural equations, graphs, probabilistic causal models) drawn upon in the contemporary debate. The aim is to fuel the reader's interest in causation, and to equip them with the resources to contribute to the debate themselves. The discussion is historically informed and outward-looking. 'Historically informed' in that concise accounts of key historical contributions to the understanding of causation set the stage for an examination of the latest research. 'Outward looking' in that illustrations are provided of how the philosophy of causation relates to issues in the sciences, law, and elsewhere. The aim is to show why the study of causation is of critical importance, besides being fascinating in its own right. Cover Title page Copyright page Elements in the Philosophy of Science Contents 1 Introduction 2 Regularity Theories of Causation 2.1 Hume 2.2 Mill 2.3 Hart and Honoré on the Cause/Condition Distinction 2.4 Mackie 2.5 Problems with the Regularity Theory 2.5.1 The Direction of Causation 2.5.2 Probabilistic Causes 2.5.3 Common Causes 3 Interlude: Some Important Background 3.1 Is Causation Really a Relation? What Are Its Relata? 3.2 How Many Relata? 3.3 Token vs Type 3.4 Aims and Method 3.4.1 Concepts vs Metaphysics 3.4.2 Causal Proliferation? 3.4.3 Reduction 4 Counterfactual Theories of Causation 4.1 Lewis’s 1973 Analysis of Causation 4.2 Early Preemption 4.3 Late Preemption 4.4 Symmetric Overdetermination 4.5 The Fragility Response 4.6 De Facto Dependence and Causal Modelling 4.6.1 Structural Equation Models 4.6.2 A Structural Equations Analysis of Causation 4.6.3 Apt Models 4.6.4 A Problem for SEA 4.6.5 Token vs Type Again 4.6.6 Interventions 5 Probabilistic Causation 5.1 Accounts of Probabilistic Causation 5.2 Difficulties 5.3 Probabilistic Causal Models 5.4 Analysing Causation in terms of Probabilistic Models 5.5 Overdetermination of Probabilities 5.6 Type Causation, Interventions, and Epistemology 5.7 Probability-Raising vs Probability-Lowering 6 Conclusion References
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