Pitt Logo LinkContact Us

Probabilistic Accounts of Inferential Justification: Liberalism and Inference to the Best Explanation

Gates, Gregory E. (2011) Probabilistic Accounts of Inferential Justification: Liberalism and Inference to the Best Explanation. Doctoral Dissertation, University of Pittsburgh.

[img]
Preview
PDF - Primary Text
Download (914Kb) | Preview

    Abstract

    I argue for three main conclusions. First, we should adopt a "probability first" approach to epistemology, which takes facts about justification for outright belief to supervene on facts about rationally permissible credence distributions. Such an approach is plausible even though standard accounts that reduce belief to credence above a threshold or invariance in conditional preferences are vulnerable to intuitive counterexamples.Second, I argue that a dogmatist response to skepticism about inferential justification is false if we adopt a probability first approach. Dogmatists hold that we might gain justification to believe E -> H for the first time when we learn E (and nothing stronger). I show that only a dynamic Keynesian model is compatible with dogmatism about inferential justification. But the main virtue of the dynamic Keynesian model--it allows for learning about fundamental evidential relationships--is by no means unique to it. I conclude that a rationalist liberalism, which holds that we are independently justified in believing E -> H whenever we are inferentially justified in believing H on the basis of E, is the best anti-skeptical account of inferential justification on most probabilistic models.Finally, I argue that the compatibilist approach to the conflict between Bayesian conditionalization and inference to the best explanation (IBE) fails. However, we anyway need to impose constraints on rational credence other than conditionalization, and we should take explanatory considerations to constrain the rationally permissible prior credence distributions. I present an account of IBE such that we should give higher conditional prior credence to H, given E, when H is the most intellectually satisfying explanation of E, and defend this account against the objection that the subjectivity of intellectual satisfaction will lead to an unacceptably permissive epistemology.


    Share

    Citation/Export:
    Social Networking:

    Details

    Item Type: University of Pittsburgh ETD
    ETD Committee:
    ETD Committee TypeCommittee MemberEmail
    Committee CoChairGupta, Anilagupta@pitt.edu
    Committee CoChairDorr, Ciancian.dorr@philosophy.ox.ac.uk
    Committee MemberAllen, Jamesjvallen@pitt.edu
    Committee MemberWilson, Markmawilson@pitt.edu
    Title: Probabilistic Accounts of Inferential Justification: Liberalism and Inference to the Best Explanation
    Status: Unpublished
    Abstract: I argue for three main conclusions. First, we should adopt a "probability first" approach to epistemology, which takes facts about justification for outright belief to supervene on facts about rationally permissible credence distributions. Such an approach is plausible even though standard accounts that reduce belief to credence above a threshold or invariance in conditional preferences are vulnerable to intuitive counterexamples.Second, I argue that a dogmatist response to skepticism about inferential justification is false if we adopt a probability first approach. Dogmatists hold that we might gain justification to believe E -> H for the first time when we learn E (and nothing stronger). I show that only a dynamic Keynesian model is compatible with dogmatism about inferential justification. But the main virtue of the dynamic Keynesian model--it allows for learning about fundamental evidential relationships--is by no means unique to it. I conclude that a rationalist liberalism, which holds that we are independently justified in believing E -> H whenever we are inferentially justified in believing H on the basis of E, is the best anti-skeptical account of inferential justification on most probabilistic models.Finally, I argue that the compatibilist approach to the conflict between Bayesian conditionalization and inference to the best explanation (IBE) fails. However, we anyway need to impose constraints on rational credence other than conditionalization, and we should take explanatory considerations to constrain the rationally permissible prior credence distributions. I present an account of IBE such that we should give higher conditional prior credence to H, given E, when H is the most intellectually satisfying explanation of E, and defend this account against the objection that the subjectivity of intellectual satisfaction will lead to an unacceptably permissive epistemology.
    Date: 27 September 2011
    Date Type: Completion
    Defense Date: 09 August 2011
    Approval Date: 27 September 2011
    Submission Date: 13 August 2011
    Access Restriction: No restriction; Release the ETD for access worldwide immediately.
    Patent pending: No
    Institution: University of Pittsburgh
    Thesis Type: Doctoral Dissertation
    Refereed: Yes
    Degree: PhD - Doctor of Philosophy
    URN: etd-08132011-145128
    Uncontrolled Keywords: Bayesian epistemology; dogmatism; epistemology; inference to the best explanation; inferential justification; rationalism
    Schools and Programs: Dietrich School of Arts and Sciences > Philosophy
    Date Deposited: 10 Nov 2011 14:59
    Last Modified: 20 Jan 2012 09:33
    Other ID: http://etd.library.pitt.edu/ETD/available/etd-08132011-145128/, etd-08132011-145128

    Actions (login required)

    View Item

    Document Downloads