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    Home/Original/inverse
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    Inverse View

    It is not the case that The inductive logic of probabilistic support functions satisfies the Criterion of Adequacy (CoA).

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

    Reasons For

    2 perspectives
    Reason for 1 of 2
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    • 1.The Likelihood Ratio Convergence Theorem assumes the true hypothesis has non-zero prior probability, but Bayesian priors are assigned before evidence.
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    • 2.If a prior probability of zero is assigned to the true hypothesis—as can occur with infinitely many competitors—convergence to truth is mathematically impossible.
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    • 3.Therefore, CoA satisfaction is conditional on prior assignment practices that the probabilistic framework itself cannot justify without circularity.
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    Reason for 2 of 2
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    • 1.Kuhn and Feyerabend demonstrate that hypothesis spaces are theory-laden, meaning what counts as a 'competitor' shifts across paradigms.
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    • 2.The Likelihood Ratio Convergence Theorem presupposes a fixed, well-defined hypothesis space that persists through evidential accumulation.
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    • 3.Because revolutionary science replaces rather than refines hypothesis spaces, convergence results apply only within paradigms, not to the scientific enterprise CoA is meant to vindicate.
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    Reasons Against

    1 perspective
    Reason against
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    • 1.The Criterion of Adequacy requires that a probabilistic inductive logic converge on the true hypothesis and away from false ones as evidence accumulates.
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    • 2.The Likelihood Ratio Convergence Theorem establishes that posterior probabilities of false competitors converge to 0 and posterior probability of the true hypothesis converges to 1.
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