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Synthese

, Volume 190, Issue 8, pp 1337–1350 | Cite as

Idealisations in normative models

  • Mark Colyvan
Article

Abstract

In this paper I discuss the kinds of idealisations invoked in normative theories—logic, epistemology, and decision theory. I argue that very often the so-called norms of rationality are in fact mere idealisations invoked to make life easier. As such, these idealisations are not too different from various idealisations employed in scientific modelling. Examples of the latter include: fluids are incompressible (in fluid mechanics), growth rates are constant (in population ecology), and the gravitational influence of distant bodies can be ignored (in celestial mechanics). Thinking of logic, epistemology, and decision theory as normative models employing various idealisations of these kinds, changes the way we approach the justification of the models in question.

Keywords

Formal epistemology Idealisations Normativity Decision theory 

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References

  1. Armstrong W. E. (1939) The Determinateness of the utility function. Economic Journal 49: 453–467CrossRefGoogle Scholar
  2. Bueno O., Colyvan M. (2011) An inferential conception of the application of mathematics. Noûs 45(2): 345–374CrossRefGoogle Scholar
  3. Colyvan M. (2004) The philosophical significance of Cox’s theorem. International Journal of Approximate Reasoning 37(1): 71–85CrossRefGoogle Scholar
  4. Colyvan M. (2008) Is probability the only coherent approach to uncertainty?. Risk Analysis 28(3): 645–652CrossRefGoogle Scholar
  5. Colyvan M., Cox D., Steele K. (2010) Modelling the moral dimension of decisions. Noûs 44(3): 503–529CrossRefGoogle Scholar
  6. Colyvan M., Justus J., Regan H. M. (2011) The conservation game. Biological Conservation 144(4): 1246–1253CrossRefGoogle Scholar
  7. Cox R. T. (1946) Probability frequency and reasonable expectation. American Journal of Physics 14: 1–13CrossRefGoogle Scholar
  8. Cox R. T. (1961) The algebra of probable inference. Johns Hopkins Press, BaltimoreGoogle Scholar
  9. Fine K. (1975) Vagueness, truth, and logic. Synthese 30: 265–300CrossRefGoogle Scholar
  10. Giaquinto M. (2002) The search for certainty: A philosophical account of foundations of mathematics. Clarendon Press, OxfordGoogle Scholar
  11. Gödel, K. (1947). What is Cantor’s continuum problem? (reprinted, revised and expanded). In P. Benacerraf & H. Putnam (Eds.), Philosophy of mathematics selected readings (2nd edn, pp. 470–485). Cambridge: Cambridge University Press.Google Scholar
  12. Hyde D. (1997) From heaps and gaps to heaps of gluts. Mind 106: 641–660CrossRefGoogle Scholar
  13. Jaynes E. T. (1988) How does the brain do plausible reasoning?. In: Erickson G. J., Smith C. R. (Eds.), Maximum entropy and bayesian methods in science and engineering. Kluwer, DordrechtGoogle Scholar
  14. Kahneman D., Slovic P., Tversky A. (1982) Judgement under uncertainty: Heuristics and biases. Cambridge University Press, CambridgeGoogle Scholar
  15. Lewis D. (1983) Philosophical papers (Vol. 1). Oxford University Press, OxfordCrossRefGoogle Scholar
  16. Lindley D. V. (1982) Scoring rules and the inevitability of probability. International Statistical Review 50: 1–26CrossRefGoogle Scholar
  17. Louise J. (2004) Relativity of value and the consequentialist umbrella. The Philosophical Quarterly 54: 518–536CrossRefGoogle Scholar
  18. Luce R. D. (1956) Semiorders and a theory of utility discrimination. Econometrica 24: 178–191CrossRefGoogle Scholar
  19. Nover H., Hájek A. (2004) Vexing expectations. Mind 113(450): 237–249CrossRefGoogle Scholar
  20. Nozick R. (1969) Newcomb’s problem and two principles of choice. In: Rescher N. (Ed.), Essays in honour of Carl G. Hempel. Reidel, DordrechtGoogle Scholar
  21. Oddie G., Milne P. (1991) Act and value: Expectation and the representability of moral theories. Theoria 57: 42–76CrossRefGoogle Scholar
  22. Priest G. (2008) An introduction to non-classical logic: From if to is, 2nd ed. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  23. Quine W. V. (1980) From a logical point of view, 2nd ed.. Harvard University Press, Cambridge, pp 20–46Google Scholar
  24. Ramsey, F. P. (1928). Truth and probability. In R. B. Braithwaite (Ed.), The foundations of mathematics and other logical essays. London: Routledge and Kegan Paul.Google Scholar
  25. Regan H. M., Colyvan M., Markovchick-Nicholls L. (2006) A formal model for consensus and negotiation in environmental management. Journal of Environmental Management 80(2): 167–176CrossRefGoogle Scholar
  26. Russell, B. (1907). The regressive method of discovering the premises of mathematics (reprinted). In D. Lackey (Ed.), Essays in analysis (pp. 272–283). London: George Allen and Unwin.Google Scholar
  27. Shafer G. (1976) A mathematical theory of evidence. Princeton University Press, PrincetonGoogle Scholar
  28. Smith N. J. J. (2008) Vagueness and degrees of truth. Oxford University Press, OxfordCrossRefGoogle Scholar
  29. Sorensen R. (1988) Blindspots. Clarendon Press, OxfordGoogle Scholar
  30. Stein, E. Without good reason: The rationality debate in philosophy and cognitive science. Oxford: Clarendon Press.Google Scholar
  31. Van Horn K. S. (2003) Constructing a logic of plausible inference: A guide to Cox’s theorem. International Journal of Approximate Reasoning 34: 3–24CrossRefGoogle Scholar
  32. Von Neumann J., Morgenstern O. (1944) Theory of games and economic behavior. Princeton University Press, PrincetonGoogle Scholar
  33. Walley P. (1991) Statistical reasoning with imprecise probabilities. Chapman and Hall, LondonGoogle Scholar
  34. Wason P. C. (1962) Psychological aspects of negation: An experimental enquiry and some practical applications. Communication Research Centre, University College London, LondonGoogle Scholar
  35. Wason P. C., Johnson-Laird P. N. (1972) Psychology of reasoning: Structure and content. Harvard University Press, CambridgeGoogle Scholar
  36. Williamson T. (1994) Vagueness. Routledge, LondonGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Sydney Centre for the Foundations of ScienceUniversity of SydneySydneyAustralia

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