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Scientific Explanation and the Causal Structure of the World
This chapter is in the book Scientific Explanation and the Causal Structure of the World
182 I Causal Forks and Common Causesnot seen how this can be accomplished, for it seems essential to have twoprocesses going in and two processes coming out in order to exploit theidea of mutual modification. I would be more than pleased if someonecould show how to explicate the concept of causal interaction in terms ofthese simpler types.CONCLUDING REMARKSThere has been considerable controversy since Hume's time regardingthe question of whether causes must precede their effects, or whether causesand effects might be simultaneous with each other. It seems to me thatthe foregoing discussion provides a reasonable resolution of this contro-versy. If we are talking about the typical cause-effect situation, which Icharacterized previously in terms of a causal process joining two distinctinteractions, then we are dealing with cases in which the cause must precedethe effect, for causal propagation over a finite time interval is an essentialfeature of cases of this type. If, however, we are dealing simply with acausal interaction—an intersection of two or more processes that produceslasting changes in each of them—then we have simultaneity, since eachprocess intersects the other at the same time. Thus it is the intersection ofthe white light pulse with the red filter that produces the red light, and thelight becomes red at the very time of its passage through the filter. Bas-ically, propagation involves lapse of time, while interaction exhibits therelation of simultaneity.Another traditional dispute has centered upon the question of whetherstatements about causal relations pertain to individual events, or whetherthey hold properly only with respect to classes of events. Again, I believe,the foregoing account furnishes a straightforward answer. I have arguedthat causal processes, in many instances, constitute the causal connectionsbetween cause and effect. A causal process is an individual entity, andsuch entities transmit causal influence. An individual process can sustaina causal connection between an individual cause and an individual effect.Statements about such relations need not be construed as disguised gen-eralizations. At the same time, it should be noted, we have used statisticalrelations to characterize conjunctive forks. Thus, strictly speaking, whenwe invoke something like the principle of the common cause, we areimplicitly making assertions involving statistical generalizations. Causalrelations, it seems to me, have both particular and general aspects.Throughout the discussion of causality, in this chapter and the precedingone, I have laid particular stress upon the role of causal processes, and Ihave even suggested the abandonment of the so-called event ontology. Itmight be asked whether it would not be possible to carry through the same
© 2020 Princeton University Press, Princeton

182 I Causal Forks and Common Causesnot seen how this can be accomplished, for it seems essential to have twoprocesses going in and two processes coming out in order to exploit theidea of mutual modification. I would be more than pleased if someonecould show how to explicate the concept of causal interaction in terms ofthese simpler types.CONCLUDING REMARKSThere has been considerable controversy since Hume's time regardingthe question of whether causes must precede their effects, or whether causesand effects might be simultaneous with each other. It seems to me thatthe foregoing discussion provides a reasonable resolution of this contro-versy. If we are talking about the typical cause-effect situation, which Icharacterized previously in terms of a causal process joining two distinctinteractions, then we are dealing with cases in which the cause must precedethe effect, for causal propagation over a finite time interval is an essentialfeature of cases of this type. If, however, we are dealing simply with acausal interaction—an intersection of two or more processes that produceslasting changes in each of them—then we have simultaneity, since eachprocess intersects the other at the same time. Thus it is the intersection ofthe white light pulse with the red filter that produces the red light, and thelight becomes red at the very time of its passage through the filter. Bas-ically, propagation involves lapse of time, while interaction exhibits therelation of simultaneity.Another traditional dispute has centered upon the question of whetherstatements about causal relations pertain to individual events, or whetherthey hold properly only with respect to classes of events. Again, I believe,the foregoing account furnishes a straightforward answer. I have arguedthat causal processes, in many instances, constitute the causal connectionsbetween cause and effect. A causal process is an individual entity, andsuch entities transmit causal influence. An individual process can sustaina causal connection between an individual cause and an individual effect.Statements about such relations need not be construed as disguised gen-eralizations. At the same time, it should be noted, we have used statisticalrelations to characterize conjunctive forks. Thus, strictly speaking, whenwe invoke something like the principle of the common cause, we areimplicitly making assertions involving statistical generalizations. Causalrelations, it seems to me, have both particular and general aspects.Throughout the discussion of causality, in this chapter and the precedingone, I have laid particular stress upon the role of causal processes, and Ihave even suggested the abandonment of the so-called event ontology. Itmight be asked whether it would not be possible to carry through the same
© 2020 Princeton University Press, Princeton

Chapters in this book

  1. Frontmatter i
  2. Contents vii
  3. Preface ix
  4. Acknowledgments xiii
  5. 1. Scientific Explanation: Three General Conceptions
  6. Introduction 1
  7. Explanation versus Description 4
  8. Other Types of Explanation 9
  9. Laplacian Explanation 11
  10. Three Basic Conceptions 15
  11. An Outline of Strategy 21
  12. 2. Statistical Explanation and Its Models
  13. Introduction 24
  14. Inductive-Statistical Explanation 27
  15. The Statistical-Relevance Approach 36
  16. 3. Objective Homogeneity
  17. Epistemic Relativization 48
  18. Randomness 55
  19. Homogeneity 60
  20. Some Philosophical Applications 72
  21. Some Philosophical Reflections 76
  22. 4. The Three Conceptions Revisited
  23. The Epistemic Conception 84
  24. The Modal Conception 111
  25. The Ontic Conception 121
  26. How These Conceptions Answer a Fundamental Question 124
  27. Conclusions 133
  28. 5. Causal Connections
  29. Basic Problems 135
  30. Two Basic Concepts 137
  31. Processes 139
  32. The 'At-At' Theory of Causal Propagation 147
  33. 6. Causal Forks and Common Causes
  34. Conjunctive Forks 158
  35. Interactive Forks 168
  36. Relations between Conjunctive and Interactive Forks 174
  37. Perfect Forks 177
  38. The Causal Structure of the World 178
  39. Concluding Remarks 182
  40. 7. Probabilistic Causality
  41. Introduction 184
  42. The Sufficiency/Necessity View 185
  43. Statistical Relevance and Probabilistic Causality 190
  44. Causality and Positive Relevance 192
  45. Causal Processes and Propensities 202
  46. 8. Theoretical Explanation
  47. Introduction 206
  48. Causal Connections and Common Causes 207
  49. Explanatory versus Inferential Principles 211
  50. The Common Cause Principle and Molecular Reality 213
  51. The Explanatory Power of Theories 227
  52. Empiricism and Realism 229
  53. 9. The Mechanical Philosophy
  54. Logic versus Mechanisms 239
  55. Explanation in Quantum Mechanics 242
  56. Explanation and Understanding 259
  57. The Causal/Mechanical Model 267
  58. The Final Contrast 276
  59. Bibliography 280
  60. Index 295
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https://doi.org/10.1515/9780691221489-031

Chapters in this book

  1. Frontmatter i
  2. Contents vii
  3. Preface ix
  4. Acknowledgments xiii
  5. 1. Scientific Explanation: Three General Conceptions
  6. Introduction 1
  7. Explanation versus Description 4
  8. Other Types of Explanation 9
  9. Laplacian Explanation 11
  10. Three Basic Conceptions 15
  11. An Outline of Strategy 21
  12. 2. Statistical Explanation and Its Models
  13. Introduction 24
  14. Inductive-Statistical Explanation 27
  15. The Statistical-Relevance Approach 36
  16. 3. Objective Homogeneity
  17. Epistemic Relativization 48
  18. Randomness 55
  19. Homogeneity 60
  20. Some Philosophical Applications 72
  21. Some Philosophical Reflections 76
  22. 4. The Three Conceptions Revisited
  23. The Epistemic Conception 84
  24. The Modal Conception 111
  25. The Ontic Conception 121
  26. How These Conceptions Answer a Fundamental Question 124
  27. Conclusions 133
  28. 5. Causal Connections
  29. Basic Problems 135
  30. Two Basic Concepts 137
  31. Processes 139
  32. The 'At-At' Theory of Causal Propagation 147
  33. 6. Causal Forks and Common Causes
  34. Conjunctive Forks 158
  35. Interactive Forks 168
  36. Relations between Conjunctive and Interactive Forks 174
  37. Perfect Forks 177
  38. The Causal Structure of the World 178
  39. Concluding Remarks 182
  40. 7. Probabilistic Causality
  41. Introduction 184
  42. The Sufficiency/Necessity View 185
  43. Statistical Relevance and Probabilistic Causality 190
  44. Causality and Positive Relevance 192
  45. Causal Processes and Propensities 202
  46. 8. Theoretical Explanation
  47. Introduction 206
  48. Causal Connections and Common Causes 207
  49. Explanatory versus Inferential Principles 211
  50. The Common Cause Principle and Molecular Reality 213
  51. The Explanatory Power of Theories 227
  52. Empiricism and Realism 229
  53. 9. The Mechanical Philosophy
  54. Logic versus Mechanisms 239
  55. Explanation in Quantum Mechanics 242
  56. Explanation and Understanding 259
  57. The Causal/Mechanical Model 267
  58. The Final Contrast 276
  59. Bibliography 280
  60. Index 295
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