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    Carmelics

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    It is not the case that Probabilistic models can express whether many low-probability events combined can outweigh even the highest-probability worlds, while plausibilistic models cannot

    ?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.Plausibilistic models using Grove sphere systems can represent infinite orderings that track cumulative evidential weight across possibility classes.
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    • 2.Spohn's ranking theory assigns negative ranks that aggregate across worlds, enabling comparative assessments structurally analogous to probabilistic summation.
      ?

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    • 3.The expressive gap between plausibilistic and probabilistic models is one of representation format, not fundamental combinatorial capacity.
      ?

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    Reason for 2 of 2
    ?
    • 1.De Finetti's representation theorem shows probability functions are limit cases of qualitative comparative probability orderings, collapsing the alleged expressive divide.
      ?

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    • 2.If plausibilistic models can be extended to comparative probability structures, the claim misidentifies a contingent modeling choice as a principled semantic limitation.
      ?

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    Reasons Against

    1 perspective
    Reason against
    ?
    • 1.Probabilistic models support aggregation of probabilities
      ?

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    • 2.Aggregated probabilities play a key role in calculations of expected utility
      ?

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    • 3.Plausibility semantics cannot express aggregated probability comparisons
      ?

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