In this essay I consider, by way of the reflections of accomplished synthetic chemists, how the experimental work of the synthetic organic chemist supports the testing, refinement, and creation of theories of organic chemistry. The role of experiments in modern Baconian sciences like organic chemistry is contrasted with their role in fields of more traditional philosophical concern, such as experimental physics.

Many explanations in molecular biology, neuroscience, and other fields of experimental biology describe mechanisms underlying phenomena of interest. These mechanistic explanations (MEx) account for higher-level phenomena in terms of causally active parts and their spatiotemporal organization. What makes such a mechanistic description explanatory? The best-developed answer, Craver's causal-mechanical account, has several weaknesses. It does not fully explicate the target of explanation, interlevel relation, or interactive nonmodular character of many biological mechanisms as we understand them. An alternative account of MEx, emphasizing interdependence among a mechanism's components (‘jointness’), remedies these difficulties.

In this article, I suggest an argument that seems to show a conflict between the reflection principle and conditionalization. In particular, I show that when the reflection principle is formulated in a standard way, the principle conflicts with Jeffrey conditionalization. And it is argued that the source of the conflict resides in an ambiguity of the standard formulation. Furthermore, I attempt to rescue the principle using Bayes factors. That is, I suggest a new formulation of the principle so as to avoid the conflict.

In this article, I compare the epistemic standing of the function-to-structure inferences found in cognitive neuroscience and of the inferences based on dissociations in neuropsychology. I argue that the former have a poorer epistemic standing than the latter.

This essay develops an account of health, the functional efficiency theory, which derives from Christopher Boorse's biostatistical theory (BST). Like the BST, the functional efficiency theory is a nonevaluative view of health, but unlike the BST, it argues that the fundamental theoretical task is to distinguish levels of efficiency with which the parts and processes within organisms and within systems within organisms function. Which of these to label as healthy or pathological is of secondary importance. Because the statistical distributions that Boorse's account relies on are distributions of functional efficiency, the functional efficiency theory arguably complements rather than challenges the BST.

This article considers the Gibbs paradox and its implications for three definitions of entropy in statistical mechanics: (i) the “classical” Boltzmann entropy (SB1); (ii) the modified Boltzmann entropy that is usually proposed in response to the paradox (SB2); and (iii) a generalized version of the latter (SB2G). It is argued that (i) notwithstanding a recent suggestion to the contrary, the paradox does imply that SB1 is not a satisfactory definition of entropy; (ii) SB2 is undermined by “second-order” versions of the paradox; and (iii) SB2G solves the paradox but is not a satisfactory definition of entropy.

In an essay recently published in this journal, Branden Fitelson argues that a variant of Miller's argument for the language dependence of the accuracy of predictions can be applied to Joyce's notion of accuracy of credences formulated in terms of scoring rules, resulting in a general potential problem for Joyce's argument for probabilism. We argue that no relevant problem of the sort Fitelson supposes arises since his main theorem and his supporting arguments presuppose the validity of nonlinear transformations of credence functions that Joyce's theory, charitably construed, would identify as invalid on the basis of the principle of simple dominance.