Gödel’s remarks concerning the ideality of time are examined. In the literature, some of these remarks have been somewhat neglected while others have been heavily criticized. In this article, I propose a clear and defensible sense in which Gödel’s work bears on the question whether there is an objective lapse of time in our world.

We make two points about dualities in string theory. The first point is that the conception of duality, which we will discuss, meshes with two dual theories being ‘gauge related’ in the general philosophical sense of being physically equivalent. The second point is a result about gauge/gravity duality that shows its relation to gauge symmetries to be subtler than one might expect: each of a certain class of gauge symmetries in the gravity theory, that is, diffeomorphisms, is related to a position-dependent symmetry of the gauge theory.

In this article I argue that structure in chemistry is a creature of abstraction: attending selectively to structural similarities, we neglect differences. There are different ways to abstract, so abstraction is interest dependent. So is structure. First, there are two different and mutually irreducible notions of structure in chemistry: bond structure and geometrical structure. Second, structure is relative to scale (of energy, time, and length): the same substance has different structures at different scales, and relationships of structural sameness and difference vary across the scales. However, these facts have no tendency to undermine structure’s claim to reality, or its metaphysical seriousness.

It is widely assumed that mechanistic explanations are causal explanations. Many prominent new mechanists endorse interventionism as the correct analysis of explanatory causal models in biology and other fields. This article argues that interventionism is not entirely satisfactory in this regard. A case study of Jacob and Monod’s operon model shows that at least some important mechanistic explanations in biology present significant contrasts with the interventionist account. This result motivates a more inclusive approach to mechanistic explanation, allowing for noncausal aspects.

What makes a measure of well-being valid? The dominant approach today, construct validation, uses psychometrics to ensure that questionnaires behave in accordance with background knowledge. Our first claim is interpretive—construct validation obeys a coherentist logic that seeks to balance diverse sources of evidence about the construct in question. Our second claim is critical—while in theory this logic is defensible, in practice it does not secure valid measures. We argue that the practice of construct validation in well-being research is theory avoidant, favoring a narrow focus on statistical tests while largely ignoring relevant philosophical considerations.

Climate change adaptation is largely a local matter, and adaptation planning can benefit from local climate change projections. Such projections are typically generated by accepting climate model outputs in a relatively uncritical way. We argue, based on the IPCC’s treatment of model outputs from the CMIP5 ensemble, that this approach is unwarranted and that subjective expert judgment should play a central role in the provision of local climate change projections intended to support decision-making.

Roman Frigg and others have developed a general epistemological argument designed to cast doubt on the capacity of a broad range of mathematical models (including many climate models) to generate “decision relevant predictions.” In this article, we lay out the structure of their argument—an argument by analogy—with an eye to identifying points at which certain epistemically significant distinctions might limit the force of the analogy. Finally, some of these epistemically significant distinctions are introduced and defended as relevant to a great many of the predictive mathematical modeling projects employed in contemporary climate science.

Many examples of calibration in climate science raise no alarms regarding model reliability. We examine one example and show that, in employing classical hypothesis testing, it involves calibrating a base model against data that are also used to confirm the model. This is counter to the ‘intuitive position’ (in favor of use novelty and against double counting). We argue, however, that aspects of the intuitive position are upheld by some methods, in particular, the general cross-validation method. How cross-validation relates to other prominent classical methods such as the Akaike information criterion and Bayesian information criterion is also discussed.