Resolving the bayesian problem of idealization

Abstract In "Bayesian Confirmation of Theories that Incorporate Idealizations", Michael Shaffer argues that, in order to show how idealized hypotheses can be confirmed, Bayesians must develop a coherent proposal for how to assign prior probabilities to counterfactual conditionals. This paper develops a Bayesian reply to Shaffer's challenge that avoids the issue of how to assign prior probabilities to counterfactuals by treating idealized hypotheses as abstract descriptions. The reply allows Bayesians to assign non-zero degrees of confirmation to idealized hypotheses and to capture the intuition that less idealized hypotheses tend to be better confirmed than their more idealized counterparts.
Keywords No keywords specified (fix it)
Categories
Options
 Save to my reading list
Follow the author(s)
My bibliography
Export citation
Find it on Scholar
Edit this record
Mark as duplicate
Revision history Request removal from index
 
Download options
PhilPapers Archive


Upload a copy of this paper     Check publisher's policy on self-archival     Papers currently archived: 5,701
External links
  •   Try with proxy.
  • Through your library Only published papers are available at libraries

    Similar books and articles

    Analytics

    Monthly downloads

    Added to index

    2009-01-28

    Total downloads

    14 ( #83,151 of 549,122 )

    Recent downloads (6 months)

    1 ( #63,361 of 549,122 )

    How can I increase my downloads?


    My notes
    Sign in to use this feature


    Discussion
    Start a new thread
    Order:
    There  are no threads in this forum
    Nothing in this forum yet.

    Other forums