Stephen Leeds

What are the objects of the so-called ‘propositional attitudes’ — belief, desire, and the like? One of the best-known accounts holds them to be sentences. According to this account — which I shall call the ‘linguistic theory’ — an analysis of the logical form of a sentence like John believes that the moon is roundwill see the word ‘that’ as a hidden pair of quotation marks: except for niceties of idiom, might be written John believes ‘the moon is round’. asserts that a certain relation, the ‘believes’-relation, holds between John and the sentence ‘the moon is round’.

In their paper "Why Gibbs Phase Averages Work--The Role of Ergodic Theory" (1980), David Malament and Sandy Zabell attempt to explain why phase averaging over the microcanonical ensemble gives correct predictions for the values of thermodynamic observables, for an ergodic system at equilibrium. Their idea is to bypass the traditional use of limit theorems, by relying on a uniqueness result about the microcanonical measure--namely, that it is uniquely stationary translation-continuous. I argue that their explanation begs questions about the relationship between thermodynamic equilibrium and statistical equilibrium; I argue in addition that any account which supports their view of the relationship between these two notions of equilibrium will likely use the limit theorems in traditional ways, and thereby bypass the explanation they offer

I argue that Earman and Norton's familiar "hole argument" raises questions as to whether GTR is a deterministic theory only given a certain assumption about determinism: namely, that to ask whether a theory is deterministic is to ask about the physical situations described by the theory. I think this is a mistake: whether a theory is deterministic is a question about what sentences can be proved within the theory. I show what these sentences look like: for interesting theories, a harmless bit of infinitary logic puts in an appearance

This paper investigates the possibility of extending the likelihood treatment of support to situations in which the evidence and the hypotheses supported by the evidence are all outcomes of a chance process. An example is when we ask how much support the observed sequence of heads and tails gives to the hypothesis that the next toss will be a head. I begin by discussing Sober’s approach to a problem of this type: that of estimating how much support the observation that I have a mind gives to the hypothesis that you do. I criticize his approach, and offer a general solution to the problem.