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    Carmelics

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    It is not the case that Probabilistic relevance requires a well-defined probability space, which itself presupposes determinate logical or causal relations between propositions.

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

    Reasons For

    1 perspective
    Reason for
    ?
    • 1.Probability spaces can be defined axiomatically without prior commitment to causal or logical structure—set theory alone suffices.
      ?

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    • 2.Empirical systems exhibit probabilistic patterns without determinate underlying logic; randomness itself may be fundamental, not derivative.
      ?

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    • 3.Relevance relations can be discovered inductively from data rather than presupposed deductively from prior logical or causal frameworks.
      ?

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    Reasons Against

    1 perspective
    Reason against
    ?
    • 1.Probability assignments require a sample space of mutually exclusive, exhaustive outcomes, which logically presupposes prior determinate distinctions.
      ?

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    • 2.Without causal or logical structure, propositions lack the definitional boundaries needed to calculate their conditional probabilities meaningfully.
      ?

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    • 3.Bayesian updating depends on identifying which propositions affect others, implying causal relations must be antecedent to probability calculations.
      ?

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