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    LoyalLoyalJusticeJustice
    Made withinDC&Austin
    Statements
    321,452
    Perspectives
    108,905
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    42
    Home/Original/inverse
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    Inverse View

    It is not the case that Embedding such assumptions into a Bayesian framework does not dissolve the problem of induction but merely relocates it to the prior specification stage.

    ?Set your confidence on the premises below to see your aggregate.

    Reasons For

    1 perspective
    Reason for
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    • 1.The problem of induction concerns justifying generalizations from finite samples; Bayesian priors address this directly by modeling uncertainty rationally.
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    • 2.Relocating an issue is progress if the relocated version is more tractable; prior specification is empirically constrainable in ways induction-at-large is not.
      ?

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    • 3.Priors need not be fully justified independently; they can be justified pragmatically through predictive success and sensitivity analysis of results to prior choice.
      ?

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    Reasons Against

    1 perspective
    Reason against
    ?
    • 1.Priors in Bayesian inference require justification independent of observed data, creating the same circularity Hume identified in induction.
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    • 2.Choosing between competing priors lacks a principled, data-independent method, merely pushing the inductive problem one level deeper.
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    • 3.Without solving how we justify initial credences, Bayesian updating cannot ground knowledge from experience—it only conditions on assumptions.
      ?

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