Advertisement

Synthese

, Volume 190, Issue 16, pp 3611–3623 | Cite as

Modeling without representation

  • Alistair M. C. Isaac
Article

Abstract

How can mathematical models which represent the causal structure of the world incompletely or incorrectly have any scientific value? I argue that this apparent puzzle is an artifact of a realist emphasis on representation in the philosophy of modeling. I offer an alternative, pragmatic methodology of modeling, inspired by classic papers by modelers themselves. The crux of the view is that models developed for purposes other than explanation may be justified without reference to their representational properties.

Keywords

Modeling Representation Pragmatism Methodology 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brainard W.: Uncertainty and the effectiveness of policy. The American Economic Review 57, 411–425 (1967)Google Scholar
  2. Caldwell B. J.: Beyond positivism: Economic methodology in the twentieth century. George Allen & Unwin, Boston, MA (1982)Google Scholar
  3. Camerer C., Thaler R. H.: Anomalies: Ultimatums, dictators and manners. The Journal of Economic Perspectives 9, 209–219 (1995)CrossRefGoogle Scholar
  4. Friedman B., Kuttner K. N.: A price target for U.S. monetary policy? Lessons from the experiene with money growth targets. Brooking Papers on Economic Activity 1996, 77–146 (1996)CrossRefGoogle Scholar
  5. Friedman, M. (1951). The effects of a full-employment policy on economic stability: A formal analysis. Reprinted in (1953) Essays in positive economics, pp. 117–132, Chicago: University of Chicago Press.Google Scholar
  6. Friedman, M. (1953). The methodology of positive economics. In Essays in positive economics (pp. 3–46). Chicago: University of Chicago PressGoogle Scholar
  7. Giere, R. N. (1988). Explaining science: A cognitive approach. Chicago, IL: University of Chicago Press.Google Scholar
  8. Godfrey-Smith P.: The strategy of model-based science. Biology and Philosophy 21, 725–740 (2006)CrossRefGoogle Scholar
  9. Hammond, J. D. (2008). Friedman’s methodology essay in context. In R. Leeson (Ed.), The anti-Keynesian tradition (pp. 78–95). Basingstoke: Palgrave Macmillan.Google Scholar
  10. Levins R.: The strategy of model building in population biology. American Scientist 54, 421–431 (1966)Google Scholar
  11. Levins, R. (1968). Evolution in changing environments. Princeton, NJ: Princeton University Press.Google Scholar
  12. Levins, R., & Lewontin, R. (1985). The dialectical biologist. Cambridge, MA: Harvard University Press.Google Scholar
  13. Mäki, U. (2009). Unrealistic assumptions and unnecessary confusions: Rereading and rewriting F53 as a realist statement. In U. Mäki (Ed.), The methodology of positive economics: Reflections on Milton Friedman’s legacy (pp. 90–116). Cambridge: Cambridge University Press.Google Scholar
  14. Mitchell D. W.: Risk aversion and optimal macro policy. The Economic Journal 89, 913–918 (1979)CrossRefGoogle Scholar
  15. Morrison, M., & Morgan, M. S. (1999). Models as mediating instruments. In M. S. Morgan & M. Morrison (Ed.), Models as mediators (pp. 10–37). Cambridge: Cambridge University Press.Google Scholar
  16. Odenbaugh J.: “The strategy of model building in population biology”. Biology and Philosophy 21, 607–621 (2006)CrossRefGoogle Scholar
  17. Schliesser E.: Galilean reflections on Milton Friedman’s ‘methodology of positive economics,’ with thoughts on Vernon Smith’s ‘economics in the laboratory’. Philosophy of the Social Sciences 35, 50–74 (2005)CrossRefGoogle Scholar
  18. Schliesser E.: Inventing paradigms, monopoly, methodology, and mythology at ‘Chicago’: Nutter, Stigler, and Milton Friedman. Studies in History and Philosophy of Science 43, 160–171 (2012)CrossRefGoogle Scholar
  19. Smith, G. E. (2002). The Methodology of the Principia. In I. B. Cohen & G. E. Smith (Eds.), The Cambridge companion to Newton (pp. 138–173). Cambridge: Cambridge University Press.Google Scholar
  20. Suppes P.: A comparison of the meaning and uses of models in mathematics and the empirical sciences. Synthese 12, 287–301 (1960)CrossRefGoogle Scholar
  21. Suppes, P. (2002). Representation and invariance of scientific structures. Stanford, CA: CSLI Publications.Google Scholar
  22. Weisberg M.: Forty years of ‘the strategy’: Levins on model building and idealization. Biology and Philosophy 21, 623–645 (2006)CrossRefGoogle Scholar
  23. Weisberg M.: Three kinds of idealization. Journal of Philosophy 104, 639–659 (2007a)Google Scholar
  24. Weisberg M.: Who is a modeler?. British Journal for the Philosophy of Science 58, 207–233 (2007b)CrossRefGoogle Scholar
  25. Wimsatt, W. C. (1987). False models as means to truer theories. In M. H. Nitecki & A. Hoffman (Eds.), Neutral models in biology (pp. 23–55) Oxford: Oxford University Press.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of PhilosophyUniversity of PennsylvaniaPhiladelphiaUSA

Personalised recommendations