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Functional Analyses, Mechanistic Explanations, and Explanatory Tradeoffs

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Recently, Piccinini and Craver have stated three theses concerning the relations between functional analysis and mechanistic explanation in cognitive sciences: No Distinctness: functional analysis and mechanistic explanation are explanations of the same kind; Integration: functional analysis is a kind of mechanistic explanation; and Subordination: functional analyses are unsatisfactory sketches of mechanisms. In this paper, I argue, first, that functional analysis and mechanistic explanations are sub-kinds of explanation by scientific (idealized) models. From that point of view, we must take into account the tradeoff between the representational/explanatory goals of generality and precision that govern the practice of model-building. In some modeling scenarios, it is rational to maximize explanatory generality at the expense of mechanistic precision. This tradeoff allows me to put forward a problem for the mechanist position. If mechanistic modeling endorses generality as a valuable goal, then Subordination should be rejected. If mechanists reject generality as a goal, then Integration is false. I suggest that mechanists should accept that functional analysis can offer acceptable explanations of cognitive phenomena.

Abstract

Recently, Piccinini and Craver have stated three theses concerning the relations between functional analysis and mechanistic explanation in cognitive sciences: No Distinctness: functional analysis and mechanistic explanation are explanations of the same kind; Integration: functional analysis is a kind of mechanistic explanation; and Subordination: functional analyses are unsatisfactory sketches of mechanisms. In this paper, I argue, first, that functional analysis and mechanistic explanations are sub-kinds of explanation by scientific (idealized) models. From that point of view, we must take into account the tradeoff between the representational/explanatory goals of generality and precision that govern the practice of model-building. In some modeling scenarios, it is rational to maximize explanatory generality at the expense of mechanistic precision. This tradeoff allows me to put forward a problem for the mechanist position. If mechanistic modeling endorses generality as a valuable goal, then Subordination should be rejected. If mechanists reject generality as a goal, then Integration is false. I suggest that mechanists should accept that functional analysis can offer acceptable explanations of cognitive phenomena.

참고문헌 (27)

  1. Anderson, J., "How Can The Human Mind Occur in the Physical Universe?" (2007), Oxford University Press
  2. Bokulich, A., "Explanatory Fictions, In Fictions in Science. Philosophical Essays on Modelling and Idealisation", pp.91~109 (2009), Routledge
  3. Bokulich, A., "How Scientific Models Can Explain", Synthese, 180(1), pp.33~45 (2011)
  4. Costello, F., "Efficient Creativity : Constraint-Guided Conceptual Combination", Cognitive Science, 24(2), pp.299~349 (2000)
  5. Craver, C., "When Mechanistic Models Explain", Synthese, 155, pp.355~376 (2006)
  6. Craver, C., "Explaining the Brain" (2007), Clarendon Press
  7. Craver, C., "Mechanisms and Natural Kinds", Philosophical Psychology, 22, pp.575~594 (2009)
  8. Cummins, R., "The World in the Head" (2010), Clarendon Press
  9. Doyle, D., "The structure of the potassium channel : molecular basis of K+ conduction and selectivity", Science, 280, pp.69~77 (1998)
  10. Elgin, M., "Cartwright of Explanation and Idealization", Erkenntnis, 57(3), pp.441~450 (2002)
  11. Giere, R., "Science without Laws" (1999), University of Chicago Press
  12. Godfrey-Smith, P., "The Strategy of Model-Based Science", Biology and Philosophy, 21, pp.725~740 (2006)
  13. Kandel, E., "Principles of Neural Science" (2006), McGraw-Hill
  14. Kaplan, D., "Explanation and Description in Computational Neuroscience", Synthese, 183, pp.339~373 (2011)
  15. Levins, R., "The Strategy of Model Building in Population Biology", American Scientist, 54(4), pp.421~431 (1966)
  16. Machamer, P., "Thinking About Mechanisms", Philosophy of Science, 67, pp.1~25 (2000)
  17. Matthewson, J., "The Structure of Tradeoffs in Model Building", Synthese, 170, pp.169~190 (2008)
  18. Morgan, M., "Models as Mediators" (1999), Cambridge University Press
  19. Piccinini, G., "Integrating Psychology and Neuroscience : Functional Analyses as Mechanisms Sketches", Synthese, 183, pp.283~311 (2011)
  20. Treisman, A., "Features and Objects in Visual Processing", Scientific American, 255, pp.106~115 (1986)
  21. Van Fraassen, B., "Laws and Symmetry" (1989), Clarendon Press
  22. Weisberg, M., "Forty Years of ‘he Strategy’", Biology and Philosophy, 21(5), pp.623~645 (2006)
  23. Weisberg, M., "Three Kinds of Idealization", Journal of Philosophy, 104(12), pp.639~659 (2007)
  24. Weiskopf, D., "Models and Mechanisms in Psychological Explanation", Synthese, 183, pp.313~338 (2011)
  25. Weiskopf, D., "The Functional Unity of Special Science Kinds", British Journal for the Philosophy of Science, 62, pp.233~258 (2011)
  26. Woodward, J., "Making Things Happen: a Theory of Causal Explanation" (2003), Oxford University Press
  27. Wright, L., "Functions", The Philosophical Review, 82(2), pp.139~168 (1973)

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