Despite the recent “epistemic turn” in the philosophy of measurement, philosophers have ignored a nearly 80-year controversy about the relationship between statistical inference and measurement theory. Some scholars maintain that measurement theory places no constraints on statistics, whereas others argue that the measurement scale (e.g., ordinal or interval) of one’s data determines which statistical methods are “permissible.” I defend an intermediate position: Even if existing measurement theory were irrelevant to statistical inference, it would be critical for scientific inference, which requires connecting statistical hypotheses to broader research hypotheses.

Eric Mandelbaum has reported some troubles with Bayesianism in cognitive science. He has brought some behavioral data to show that belief updating in humans is fundamentally Bayesian perverse. I argue that the behaviors that he seeks to explain do not undermine Bayesian accounts of belief updating and can instead be explained as idiosyncratic consequences of an appropriately bounded implementation of a Bayesian-normative belief-updating system.

This paper presents a new problem for the inference rule commonly known as “inference to the best explanation” (IBE). The problem is that uncertainty about parts of one’s evidence may undermine the inferrability of a hypothesis that would provide the best explanation of that evidence, especially in cases where there is an alternative hypothesis that would provide a better explanation of only the more certain pieces of evidence. A potential solution to the problem is sketched, in which IBE is generalized to handle uncertain evidence by invoking a notion of evidential robustness.

Previous work on the evolution of the indicative–imperative distinction in signaling games has focused on either the cognitive processes used by signaling agents or information carried by messages. In this paper, I use a simple signaling game model to demonstrate that an overlooked feature of the indicative–imperative distinction can be learned. This overlooked feature is the fact that the indicative–imperative distinction is often marked in natural languages.

Del Santo and Gisin have recently argued that classical mechanics exhibits indeterminacy and that by treating the observables of classical mechanics with real number precision we introduce hidden variables that restore determinacy. In this article we introduce the conceptual machinery required to critically evaluate these claims. We present a characterization of indeterminacy which can capture both quantum indeterminacy and the classical indeterminacy Del Santo and Gisin propose. This allows us to show that there is an important difference between the two: their classical indeterminacy can be resolved with hidden variables in a manner which is not possible for quantum indeterminacy.

Philosophers have been drawing their attention to the metaphysics of symmetries. Most have taken a Closed System View, that is, the metaphysical assumption that closed systems are ontologically fundamental. In this article, I explore the consequences of adopting a different perspective, the Open System View, according to which open systems are regarded as ontologically fundamental. I argue that by doing so, our metaphysical understanding of symmetries changes substantially in three respects: Epistemic approaches are favored, ontic approaches should change the set of physical symmetries regarded as fundamental, and the metaphysical connection between conservation principles and symmetries is weaker than thought.

Subject to techniques of perturbative renormalization, the Standard Model makes empirical predictions that are stupendously successful. But also deeply mysterious. Not every quantum field theory (qft) is renormalizable. Indeed, most aren’t. The mystery is: Why should we be so lucky, that we live in a world governed by a renormalizable qft? I explicate this Renormalizability Puzzle, and explain why Renormalization Group (RG) approaches are widely thought to resolve it. Looking under the hood of the RG resolution, I identify a load-bearing element that might not be adequate to the explanatory burden the RG resolution places upon it.