Synthese

pp 1–23 | Cite as

Explanatory schema and the process of model building

Article
  • 35 Downloads

Abstract

In this paper, we argue that rather than exclusively focusing on trying to determine if an idealized model fits a particular account of scientific explanation, philosophers of science should also work on directly analyzing various explanatory schemas that reveal the steps and justification involved in scientists’ use of highly idealized models to formulate explanations. We develop our alternative methodology by analyzing historically important cases of idealized statistical modeling that use a three-step explanatory schema involving idealization, mathematical operation, and explanatory interpretation.

Keywords

Explanation Modeling Idealization 

Notes

Acknowledgements

We would like to thank James Woodward, Robert Batterman, and two annonymous reviewers for there helpful feedback on previous versions of this article.

References

  1. Ariew, A., Rice, C., & Rohwer, Y. (2015). Autonomous statistical explanations and natural selection. The British Journal for the Philosophy of Science, 66(3), 635–658.CrossRefGoogle Scholar
  2. Ariew, A., Rohwer, Y., & Rice, C. (2017). Galton, reversion and the quincunx: The rise of statistical explanation. Studies in History and Philosophy of Biological and Biomedical Sciences, 66, 63–72.CrossRefGoogle Scholar
  3. Batterman, R. W. (2002). The devil in the details: Asymptotic reasoning in explanation, reduction, and emergence. Oxford: Oxford University Press.Google Scholar
  4. Batterman, R. W., & Rice, C. (2014). Minimal model explanations. Philosophy of Science, 81(3), 349–376.CrossRefGoogle Scholar
  5. Bokulich, A. (2011). How scientific models can explain. Synthese, 180, 33–45.CrossRefGoogle Scholar
  6. Bokulich, A. (2012). Distinguishing explanatory from nonexplanatory fictions. Philosophy of Science, 79, 725–737.CrossRefGoogle Scholar
  7. Bromberger, S. (1966). Questions. The Journal of Philosophy, 63(20), 597–606.CrossRefGoogle Scholar
  8. Charnov, E. (1982). The theory of sex allocation. Princeton, NJ: Princeton University Press.Google Scholar
  9. Craver, C. (2006). When mechanistic models explain. Synthese, 153, 355–376.CrossRefGoogle Scholar
  10. Craver, C. F. (2007). Explaining the brain: Mechanisms and the mosaic unity of neuroscience. Oxford: Oxford University Press.CrossRefGoogle Scholar
  11. Fisher, R. A. (1922). On the dominance ratio. Proceeding of the Royal Society of Edinburgh, V, 43, 321–341.Google Scholar
  12. Fisher, R. A. (1930). The genetical theory of natural selection. Oxford: Clarendon Press.CrossRefGoogle Scholar
  13. Friedman, M. (1974). Explanation and scientific understanding. Journal of Philosophy, 71, 5–19.CrossRefGoogle Scholar
  14. Galton, F. (1877). Typical laws of heredity. Nature, 15, 492–495, 512-514, 532-533.CrossRefGoogle Scholar
  15. Galton, F. (1892). Hereditary genius: An inquiry into its laws and consequences. New York: Macmillan and Co.Google Scholar
  16. Godfrey-Smith, P. (2006). The strategy of model-based science. Biology & Philosophy, 21(5), 725–740.CrossRefGoogle Scholar
  17. Hacking, I. (1990). Taming of chance. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  18. Hempel, C. (1965). Aspects of scientific explanation. New York: Free Press.Google Scholar
  19. Hughes, R. I. G. (1997). Models and representation. Philosophy of Science, 64, S325–S336.CrossRefGoogle Scholar
  20. Kadanoff, L. P. (2013). Theories of matter: Infinities and renormalization. In R. Batterman (Ed.), The oxford handbook of philosophy of physics (pp. 141–188). Oxford: Oxford University Press.Google Scholar
  21. Kitcher, P. (1981). Explanatory unification. Philosophy of Science, 48(4), 507–531.CrossRefGoogle Scholar
  22. Lewis, D. (1986). Causal Explanation. In Philosophical Papers (Vol. II). Oxford: Oxford University Press.Google Scholar
  23. Lange, M. (2012). What makes a scientific explanation distinctively mathematical? The British Journal for the Philosophy of Science, 64(3), 485–511.CrossRefGoogle Scholar
  24. Lange, M. (2013). Really statistical explanations and genetic drift. Philosophy of Science, 80(2), 169–188.CrossRefGoogle Scholar
  25. Matthen, M., & Ariew, A. (2002). Two ways of thinking about fitness and natural selection. Journal of Philosophy, 99(2), 55–83.CrossRefGoogle Scholar
  26. Matthen, M., & Ariew, A. (2009). Selection and causation. Philosophy of Science, 76, 201–224.CrossRefGoogle Scholar
  27. Moore, T. A. (2003). Six ideas that shaped physics. Unit T: Some processes are irreversible (2nd ed.). New York, NY: McGraw-Hill.Google Scholar
  28. Morrison, M. (1996). Physical models and biological contexts. Philosophy of Science, 64, S315–S324.CrossRefGoogle Scholar
  29. Morrison, M. (2004). Population genetics and population thinking: Mathematics and the role of the individual. Philosophy of Science, 71, 1189–1200.CrossRefGoogle Scholar
  30. Morrison, M. (2015). Reconstruction reality: Models, mathematics, and simulations. Oxford: Oxford University Press.CrossRefGoogle Scholar
  31. Pincock, C. (2007). A role for mathematics in the physical sciences. Noûs, 41, 253–275.CrossRefGoogle Scholar
  32. Pincock, C. (2012). Mathematics and scientific representation. Oxford: Oxford University Press.CrossRefGoogle Scholar
  33. Potochnik, A. (2007). Optimality modeling and explanatory generality. Philosophy of Science, 74(5), 680–691.CrossRefGoogle Scholar
  34. Potochnik, A. (2009). Optimality modeling in a suboptimal world. Biology and Philosophy, 24(2), 183–197.CrossRefGoogle Scholar
  35. Railton, P. (1981). Probability, explanation, and information. Synthese, 48, 233–256.CrossRefGoogle Scholar
  36. Reutlinger, A. (2016). Is there a monistic theory of causal and noncausal explanations?. The counterfactual theory of scientific explanation. Philosophy of Science.  https://doi.org/10.1086/687859.
  37. Rice, C. (2012). Optimality Explanations: A plea for an alternative approach. Biology and Philosophy, 27(5), 685–703.CrossRefGoogle Scholar
  38. Rice, C. (2015). Moving beyond causes: Optimality models and scientific explanation. Noûs, 49(3), 589–615.CrossRefGoogle Scholar
  39. Rice, C. (2017). Idealized models, holistic distortions, and universality. Synthese.  https://doi.org/10.1007/s11229-017-1357-4.
  40. Rohwer, Y., & Rice, C. (2013). Hypothetical pattern idealization and explanatory models. Philosophy of Science, 80(3), 334–355.CrossRefGoogle Scholar
  41. Rohwer, Y., & Rice, C. (2016). How are models and explanations related? Erkenntnis, 81(5), 1127–1148.CrossRefGoogle Scholar
  42. Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.Google Scholar
  43. Sober, E. (1980). Evolution, population thinking, and essentialism. Philosophy of Science, 47, 350–383.CrossRefGoogle Scholar
  44. Sober, E. (1983). Equilibrium explanation. Philosophical Studies, 43, 201–210.CrossRefGoogle Scholar
  45. Stigler, S. (2010). Darwin, Galton and the statistical enlightenment. The Journal of the Royal Statistical Society, 173(3), 469–482.CrossRefGoogle Scholar
  46. Strevens, M. (2004). The causal and unification approaches to explanation unified–causally. Noûs, 38(1), 154–176.CrossRefGoogle Scholar
  47. Strevens, M. (2009). Depth: An account of scientific explanation. Cambridge, MA: Harvard University Press.Google Scholar
  48. Walsh, D. M., Lewens, T., & Ariew, A. (2002). Trials of life: Natural selection and random drift. Philosophy of Science, 72, 311–333.Google Scholar
  49. Weisberg, M. (2007a). Three kinds of idealization. Journal of Philosophy, 104(12), 639–659.CrossRefGoogle Scholar
  50. Weisberg, M. (2007b). Who is a modeler? The British Journal for the Philosophy of Science, 58(2), 207–233.CrossRefGoogle Scholar
  51. Weisberg, M. (2013). Simulation and similarity: Using models to understand the world. Oxford: Oxford University Press.CrossRefGoogle Scholar
  52. Woodward, J. (2003). Making things happen: A theory of causal explanation. Oxford: Oxford University Press.Google Scholar
  53. Woody, A. (2015). Re-orienting discussion of scientific explanation: A functional perspective. Studies in History and Philosophy of Science, 52, 79–87.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PhilosophyBryn Mawr CollegeBryn MawrUSA
  2. 2.Department of Humanities and Social SciencesOregon Institute of TechnologyKlamath FallsUSA
  3. 3.Department of PhilosophyUniversity of MissouriColumbiaUSA

Personalised recommendations