Book contents
- Frontmatter
- Contents
- List of Figures
- Acknowledgments
- Introduction: Causation and its Asymmetries
- 1 Metaphysical Pictures and Wishes
- 1* Transfer Theories
- 2 Is Causation a Relation Among Events?
- 3 Causation, Regularities, and Time: Hume's Theory
- 4 Causation and Independence
- 4* Causation, Independence, and Causal Connection
- 5 Agency Theory
- 5* Causal Generalizations and Agency
- 6 The Counterfactual Theory
- 6* Independence and Counterfactual Dependence
- 7 Counterfactuals, Agency, and Independence
- 7* Agency, Counterfactuals, and Independence
- 8 Causation, Explanation, and Laws
- 8* Causation, Explanation, and Independent Alterability
- 9 Probabilistic Causation
- 10 Causation and Conditional Probabilities
- 10* Causal Graphs and Conditional Probabilistic Dependencies
- 11 Intervention, Robustness, and Probabilistic Dependence
- 11* Interventions and Conditional Probabilities
- 12 Operationalizing and Revising the Independence Theory
- 12* Probability Distributions and Causation
- 13 Complications and Conclusions
- Appendix A Alphabetical List of Propositions
- Appendix B List of Theorems
- References
- Index
Appendix B - List of Theorems
Published online by Cambridge University Press: 20 April 2010
- Frontmatter
- Contents
- List of Figures
- Acknowledgments
- Introduction: Causation and its Asymmetries
- 1 Metaphysical Pictures and Wishes
- 1* Transfer Theories
- 2 Is Causation a Relation Among Events?
- 3 Causation, Regularities, and Time: Hume's Theory
- 4 Causation and Independence
- 4* Causation, Independence, and Causal Connection
- 5 Agency Theory
- 5* Causal Generalizations and Agency
- 6 The Counterfactual Theory
- 6* Independence and Counterfactual Dependence
- 7 Counterfactuals, Agency, and Independence
- 7* Agency, Counterfactuals, and Independence
- 8 Causation, Explanation, and Laws
- 8* Causation, Explanation, and Independent Alterability
- 9 Probabilistic Causation
- 10 Causation and Conditional Probabilities
- 10* Causal Graphs and Conditional Probabilistic Dependencies
- 11 Intervention, Robustness, and Probabilistic Dependence
- 11* Interventions and Conditional Probabilities
- 12 Operationalizing and Revising the Independence Theory
- 12* Probability Distributions and Causation
- 13 Complications and Conclusions
- Appendix A Alphabetical List of Propositions
- Appendix B List of Theorems
- References
- Index
Summary
Theorem 4.1 (p. 81) T and CC entail that if a causes b, then everything causally connected to a and distinct from b is causally connected to b.
Theorem 4.2 (p. 81) Given T and CC, if a is distinct from b and not causally connected to b, then it is not causally connected to any cause of b.
Theorem 4.3 (p. 82) CC, I, and T entail A.
Theorem 4.4 (p. 84) CC and I imply that if a is causally connected to b and everything casually connected to a and distinct from b is causally connected to b, then a causes b.
Theorem 4.5 (p. 84) T, CC, and I entail CP.
Theorem 4.6 (p. 84) T, CC, and I entail CP.
Theorem 4.7 (p. 85) T, CC, CP, and A (asymmetry) imply I.
Theorem 5.1 (p. 107) DHIg, PIg, Tg, and PPg imply ATg.
Theorem 5.2 (p. 108) DHIg, CCg, Tg, and ATg entail CPg.
Theorem 5.3 (p. 108) DIg, PIg, Tg, and PPg imply ATg.
Theorem 5.4 (p. 108) DIg, CCg, Tg, and ATg entails CPg.
Theorem 5.5 (p. 108) DIg, PIg, CCg, and Tg entail CPg.
Theorem 5.6 (p. 109) Given CCg and NICg, Igg is entailed by DIg and PIg.
Theorem 5.7 (p. 110) CCg, PIg, DIg, and NICg entail Ig.
Theorem 6.1 (p. 135) SIM, CDCC, and I imply that individual causes will not be counterfactually dependent on individual effects and effects of a common asymmetric cause will not be counterfactually dependent on one another.
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- Causal Asymmetries , pp. 282 - 284Publisher: Cambridge University PressPrint publication year: 1998