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Inverse View
It is not the case that A rule need not be algorithmic or deductively certain to count as 'acceptable'; probabilistic inferential norms meet the standard for inductive logic.
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Reason for
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1.
Probabilistic norms require a well-defined probability model, which itself needs justification—pushing the problem back a level.
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2.
Without algorithmic or deductive grounding, probabilistic rules risk collapsing into pragmatism rather than logic proper.
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3.
Accepting vague probabilistic standards as 'rules' conflates useful heuristics with genuine normative constraints on reasoning.
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Reasons Against
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Reason against
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1.
Inductive reasoning is essential to empirical inquiry, yet deductive certainty is impossible in most real-world contexts.
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2.
A rule's acceptability should match its domain: probabilistic norms are appropriate for uncertain domains like science.
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3.
Excluding probabilistic rules would eliminate the rational standards actually governing successful scientific inference.
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