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    Made withinDC&Austin
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    Home/Original/inverse
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    Inverse View

    It is not the case that A hypothesis need not be deductively related to evidence in order to bear on it probabilistically

    ?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.Probabilistic relevance requires a well-defined probability space, which itself presupposes determinate logical or causal relations between propositions.
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    • 2.Without deductive or lawlike connections grounding the probability assignments, the numerical values become arbitrary and lose objective epistemic significance.
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    • 3.This objection draws on Keynes's logical theory of probability, where probability is a logical relation requiring objective structural constraints.
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    Reason for 2 of 2
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    • 1.Glymour's bootstrap confirmation theory shows that evidential support requires deductive derivability of test implications from hypotheses plus background conditions.
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    • 2.Purely probabilistic relevance without deductive anchoring permits confirmation paradoxes where irrelevant hypotheses gain spurious support from unrelated evidence.
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    • 3.The Old Evidence Problem identified by Garber and Glymour shows Bayesian probabilistic relevance fails when evidence is already known, exposing its deductive dependency.
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    Reasons Against

    1 perspective
    Reason against
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    • 1.A hypothesis may itself be an explicitly probabilistic or statistical hypothesis
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    • 2.An auxiliary statistical hypothesis in the background b may connect a hypothesis to the evidence
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    • 3.The connection between a hypothesis and evidence may be loose or imprecise yet still objective enough for evidential evaluation
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    Strongest counterpoint
    Explore the most compelling reason on the other side.