Abstract
Inference to the Best Explanation (IBE) and Bayesianism are our two most prominent theories of scientific inference. Are they compatible? Van Fraassen famously argued that they are not, concluding that IBE must be wrong since Bayesianism is right. Writers since then, from both the Bayesian and explanationist camps, have usually considered van Fraassen’s argument to be misguided, and have plumped for the view that Bayesianism and IBE are actually compatible. I argue that van Fraassen’s argument is actually not so misguided, and that it causes more trouble for compatibilists than is typically thought. Bayesianism in its dominant, subjectivist form, can only be made compatible with IBE if IBE is made subservient to conditionalization in a way that robs IBE of much of its substance and interest. If Bayesianism and IBE are to be fit together, I argue, a strongly objective Bayesianism is the preferred option. I go on to sketch this objectivist, IBE-based Bayesianism, and offer some preliminary suggestions for its development.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Armstrong, D. (1983). What is a law of nature. Cambridge University Press.
Carnap, R. (1950). Logical foundations of probability. University of Chicago Press.
Christensen, D. (2004). Putting logic in its place. Oxford University Press.
Douven, I. (1999). Inference to the best explanation made coherent. Philosophy of Science, 66.
Goodman, N. (1954). Fact, fiction, and forecast. The Athlone Press.
Greaves H., Wallace D. (2006). Justifying conditionalization: Conditionalization maximizes expected epistemic utility. Mind 115: 607–632
Jaynes E.T. (1968). Prior probabilities. IEEE Transactions on systems and cybernetics SSC-4(3): 227–241
Jeffrey R. (1970). Dracula meets wolfman: Acceptance vs. partial belief. In: Swain M. (eds) Induction, acceptance, and rational belief. Dordrecht, Reidel
Jeffrey R. (1983). Bayesianism with a human face. Minnesota studies in the philosophy of science 10: 133–156
Lange, M. (1999). Calibration and the epistemological role of Bayesian conditionalization. Journal of Philosophy XCVI.
Levi, I. (1980). The enterprise of knowledge: An essay on knowledge, credal probability, and chance. The MIT Press.
Lewis, D. (1973). Counterfactuals. Harvard University of Press.
Lewis, D. (1980). A subjectivist’s guide to objective chance. In R. C. Jeffrey (Ed.), Studies in inductive logic and probability (Vol. II). University of California Press.
Lipton, P. (2004). Inference to the best explanation (2nd Ed.). Routledge.
Maher, P. (1993). Betting on theories. Cambridge University Press.
McGrew, T. (2003). Confirmation, heuristics, and explanatory reasoning. British Journal for the Philosophy of Science, 54.
Okasha, S. (2000). Van Fraassen’s critique of inference to the best explanation. Studies in the history and philosophy of science, 31(4).
Teller, P. (1973). Conditionalization and observation. Synthese, 26.
Tregear, M. (2004). Utilising explanatory factors in induction. British Journal for the Philosophy of Science, 55.
van Fraassen B. (1984). Belief and the will. The Journal of Philosophy 81(5): 235–256
van Fraassen, B. (1989). Laws and symmetry. Oxford University Press.
van Fraassen B. (1995). Belief and the problem of Ulysses and the Sirens. Philosophical studies 77: 7–37
van Fraassen, B. (1999). Conditionalization: A new argument for. Topoi, 18.
White, R. (2005). Explanation as a guide to induction. Philosopher’s imprint, 5(2).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Weisberg, J. Locating IBE in the Bayesian framework. Synthese 167, 125–143 (2009). https://doi.org/10.1007/s11229-008-9305-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11229-008-9305-y