Ignorance, Milk and Coffee: Can Epistemic States be Causally-Explanatorily Relevant in Statistical Mechanics?
Foundation of Science (2021)
AbstractIn this paper I will evaluate whether some knowledge states that are interpretatively derived from statistical mechanical probabilities could be somehow relevant in actual practices, as famously rejected by Albert (2000). On one side, I follow Frigg (2010a) in rejecting the causal relevance of knowledge states as a mere byproduct of misinterpreting this theoretical field. On the other side, I will argue against Uffink (2011) that probability-represented epistemic states cannot be explanatorily relevant, because (i) probabilities cannot faithfully represent significant epistemic states, and (ii) those states cannot satisfactorily account for why an agent should theoretically believe or expect something.
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