Bayesian likelihoodism, as developed by Sober, requires that evidential weight track likelihood ratios at the most specific evidential level available, not merely general patterns.

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Bayesian likelihoodism(the main philosophical position being discussed): A way of thinking about evidence that focuses on how likely our observations are under different hypotheses—basically, which explanation makes what we actually see most probable.
Evidential weight(in discussions about justification and reasoning): How much a piece of evidence should count toward proving or disproving something—whether it's strong proof or weak proof.
Sober(named philosopher being referenced): Elliott Sober is a philosopher of science who developed important arguments about how to compare different explanations of why things exist or happen the way they do.
Specificity (in evidential level)(the statement emphasizes using the most specific evidence available): How precise or detailed the evidence is; more specific evidence is narrower and more tailored to particular cases, rather than vague or general.

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