This article analyzes the recent debate surrounding inclusive fitness and argues that certain limitations ascribed to it by critics—such as requiring weak selection or providing dynamically insufficient models—are better thought of as limitations of the methodological framework most often used with inclusive fitness (quantitative genetics). In support of this, I show how inclusive fitness can be used with the replicator dynamics (of evolutionary game theory, a methodological framework preferred by inclusive fitness critics). I conclude that much of the debate is best understood as being about the orthogonal issue of using abstract versus idealized models.

This article uses the case study of ethnobiological classification to develop a positive and a negative thesis about the state of natural kind debates. On the one hand, I argue that current accounts of natural kinds can be integrated in a multidimensional framework that advances understanding of classificatory practices in ethnobiology. On the other hand, I argue that such a multidimensional framework does not leave any substantial work for the notion “natural kind” and that attempts to formulate a general account of naturalness have become an obstacle to understanding classificatory practices.

Gordon Belot argues that Bayesian theory is epistemologically immodest. In response, we show that the topological conditions that underpin his criticisms of asymptotic Bayesian conditioning are self-defeating. They require extreme a priori credences regarding, for example, the limiting behavior of observed relative frequencies. We offer a different explication of Bayesian modesty using a goal of consensus: rival scientific opinions should be responsive to new facts as a way to resolve their disputes. Also we address Adam Elga’s rebuttal to Belot’s analysis, which focuses attention on the role that the assumption of countable additivity plays in Belot’s criticisms.

While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to explore broad conditions under which (approximately) Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics.

In this article, I examine the relationship between physical quantities and physical states in quantum theories. I argue against the claim made by Arageorgis that the approach to interpreting quantum theories known as Algebraic Imperialism allows for “too many states.” I prove a result establishing that the Algebraic Imperialist has very general resources that she can employ to change her abstract algebra of quantities in order to rule out unphysical states.

In this article, I evaluate Hartmann and Fitelson’s solution to the Bayesian problem of old evidence by applying it to an early stage in the development of quantum theory. I argue that this case study suggests that whether old evidence is anomalous affects its support for a hypothesis. I introduce and defend two formal assumptions to accommodate this idea. This analysis not only explicates an important historical example, but it also shows that the given solution captures the intuitive importance of “surprising” evidence that has previously been problematic in the context of old evidence.

In this article, I offer a partial analysis of the role of values in qualitative data collection in social research. The partial analysis shows that nonepistemic values have both required and permissible roles to play during this phase of research. By appeal to the analysis, I reject the ideal of value-free science as applied to qualitative data collection, and I demonstrate why two alternative ideals should likewise be dismissed as standards for values in qualitative data collection. Also, I briefly discuss the extent to which the partial analysis carries over to quantitative data collection in social research.

Inmaculada de Melo-Martín and Kristen Intemann consider whether, from the perspective of the argument from inductive risk, ethical and political values might be logically, epistemically, pragmatically, or ethically necessary in the “core” of scientific reasoning. In each case, they argue that there are significant conceptual problems. In this comment, employing regulatory uses of high-throughput toxicology at the US Environmental Protection Agency as a case study, I respond to some of their claims about the notion of “pragmatic necessity.” I conclude that, while an inductive risk framework has some significant limitations, it is still conceptually and rhetorically valuable.