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    Embedding such assumptions into a Bayesian framework does... — Carmelics
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    Challenges→Analogical reasoning can provide inductive support within Bayesian epistemology without incurring the logical difficulties of ampliative rules

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

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    Reasons For

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    • 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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    Reasons Against

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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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    Related

    Analogical reasoning can provide inductive support within Bayesian epistemology ...Choosing between competing priors lacks a principled, data-independent method, m...Priors in Bayesian inference require justification independent of observed data,...Priors need not be fully justified independently; they can be justified pragmati...
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    Relocating an issue is progress if the relocated version is more tractable; prio...The problem of induction concerns justifying generalizations from finite samples...Without solving how we justify initial credences, Bayesian updating cannot groun...

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