Competing accounts of contrastive coherence
- 139 Downloads
The proposition that Tweety is a bird coheres better with the proposition that Tweety has wings than with the proposition that Tweety cannot fly. This relationship of contrastive coherence is the focus of the present paper. Based on recent work in formal epistemology we consider various possibilities to model this relationship by means of probability theory. In a second step we consider different applications of these models. Among others, we offer a coherentist interpretation of the conjunction fallacy.
KeywordsContrastivism Coherence Probability Confirmation Bayesian epistemology Conjunction fallacy
This work was supported by Grant SI 1731/1-1 to Mark Siebel from the Deutsche Forschungsgemeinschaft (DFG) as part of the priority program “New Frameworks of Rationality” (SPP 1516).
- Blauw, M. (Ed.). (2013). Contrastivism in philosophy. New York: Routledge.Google Scholar
- BonJour, L. (1985). The structure of empirical knowledge. Cambridge: Harvard University Press.Google Scholar
- Bovens, L., & Hartmann, S. (2003). Bayesian epistemology. Oxford: Oxford University Press.Google Scholar
- Chart, D. (2001). Inference to the best explanation, Bayesianism, and feminist bank tellers. Online-paper. http://philsci-archice.pitt.edu/documents/disk0/00/00/03/22/.
- Crupi, V., Festa, R., & Buttasi, C. (2010). Towards a grammar of Bayesian confirmation. In M. Surez, M. Dorato, & M. Rdei (Eds.), Epistemology and methodology of science (pp. 73–93). Berlin: Springer.Google Scholar
- de Finetti, B. ( 1980). Foresight: Its logical laws, its subjective sources. In H. E. Kyburg, Jr. & H. E. Smokler (Eds.), Studies in subjective probability (2nd ed., pp. 53–118). Huntington, NY: Robert E. Krieger.Google Scholar
- Fitelson, B. (2003). A probabilistic theory of coherence. Analysis, 63, 194–199.Google Scholar
- Gigerenzer, G. (1994). Why the distinction between single-event probabilities and frequencies is important for psychology (and vice versa). In G. Wright & P. Ayton (Eds.), Subjective probability (pp. 129–161). New York: Wiley.Google Scholar
- Glass, D. H. (2002). Coherence, explanation, and Bayesian networks. In M. ONeill, et al. (Eds.), Artificial intelligence and cognitive science (pp. 177–182). Berlin: Springer.Google Scholar
- Good, I. J. (1960). Weight of evidence, corroboration, explanatory power, information and the utility of experiments. Journal of the Royal Statistical Society (Series B), 22, 319–331.Google Scholar
- Grice, H. P. (1975). Logic and conversation. Studies in the way of words (pp. 22–40). Cambridge, MA: Harvard University Press.Google Scholar
- Joyce, J. (2004). Bayes’s theorem. In E. N. Zalta (Ed.). The Stanford encyclopedia of philosophy (Summer 2004 ed.). http://plato.stanford.edu/archives/sum2004/entries/bayes-theorem/.
- Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of representativeness. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases. Cambridge: Cambridge University Press.Google Scholar
- Lipton, P. (1990). Contrastive explanation. In D. Knowles (Ed.), Explanation and its limits (pp. 247–266). Cambridge: Cambridge University Press.Google Scholar
- Ramsey, F. P. (1926). Truth and probability. In H. E. Kyburg Jr & H. E. Smokler (Eds.), Studies in subjective probability (2nd ed., pp. 23–52). Huntington, NY: R. E. Krieger. 1980.Google Scholar
- Reichenbach, H. (1949). The theory of probability. Berkeley: University of California Press.Google Scholar
- Royal, R. (1997). Statistical evidence: A likelihood paradigm. London: Chapman and Hall.Google Scholar
- Schippers, M. (2014). Probabilistic measures of coherence. From adequacy constraints towards pluralism. Synthese, 191, 3821–3845.Google Scholar
- Shogenji, T. (2012). The degree of epistemic justification and the conjunction fallacy. Synthese, 184, 29–48.Google Scholar
- Siebel, M. (2003). There’s something about Linda: Probability, coherence and rationality. Unpublished manuscript.Google Scholar
- von Mises, R. (1957). Probability, statistics and truth. New York: Macmillan.Google Scholar