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    In models where outcome probabilities depend on distant o... — Carmelics
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    Challenges→Parameter dependence is a necessary and sufficient condition for controllable probabilistic dependence in models where measurement outcome probabilities depend only on the pair's state and apparatus settings

    In models where outcome probabilities depend on distant outcomes (not just settings), signaling constraints are violated by outcome dependence, not parameter dependence alone.

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    Reasons For

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    Reason for
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    • 1.Outcome dependence on distant events creates non-local correlations that violate Bell-type inequalities independent of parameter assignments.
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    • 2.Signaling constraints arise from the structure of outcome correlations, not merely from how parameters are distributed or chosen.
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    • 3.Models distinguishing outcome-dependence from parameter-dependence better identify which causal mechanisms actually violate locality.
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    Reasons Against

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    • 1.Parameter dependence and outcome dependence are not cleanly separable—all outcome correlations reduce to parameter specifications in formal models.
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    • 2.The distinction lacks empirical content: any testable violation of signaling constraints involves both parameter and outcome relationships equally.
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    Connections

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    Causation1 linkedModality & Possibility1 linked

    Related

    Models distinguishing outcome-dependence from parameter-dependence better identi...Outcome dependence on distant events creates non-local correlations that violate...Parameter dependence and outcome dependence are not cleanly separable—all outcom...Parameter dependence is a necessary and sufficient condition for controllable pr...
    +2 moreShow less
    Signaling constraints arise from the structure of outcome correlations, not mere...The distinction lacks empirical content: any testable violation of signaling con...

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