Much of the literature on values in science is limited in its perspective because it focuses on the role of values in individual scientists’ decision making, thereby ignoring the context of scientific collaboration. I examine the epistemic structure of scientific collaboration and argue that it gives rise to two arguments showing that moral and social values can legitimately play a role in scientists’ decision to accept something as scientific knowledge. In the case of scientific collaboration some moral and social values are properly understood to be extrinsic epistemic values, that is, values that promote the attainment of scientific knowledge.

This article presents an account of the biological populations that can undergo paradigmatic natural selection. I argue for, and develop Peter Godfrey-Smith’s claim that reproductive competition is a core attribute of such populations. However, as Godfrey-Smith notes, it is not the only important attribute. I suggest what the missing element is, co-opting elements of Alan Templeton’s notion of exchangeability. The final framework is then compared to two recent discussions regarding biological populations proposed by Roberta Millstein and Jacob Stegenga.

Recently, biologists have argued that data-driven biology fosters a new scientific methodology, namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data-driven studies can be included in the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful generalizations to complement the procedure of prioritization. Overall, this article aims to shed light on the structure of contemporary research in molecular biology.

Understanding the dynamics of information is crucial to many areas of research, both inside and outside of philosophy. Using computer simulations of three kinds of information, germs, genes, and memes, we show that the mechanism of information transfer often swamps network structure in terms of its effects on both the dynamics and the fitness of the information. This insight has both obvious and subtle implications for a number of questions in philosophy, including questions about the nature of information, whether there is genetic information, and how to arrange scientific communities.

The aim of this article is to develop an argument against metaphysical debates about the existence of human races. I argue that the ontology of race is underdetermined by both empirical and nonempirical evidence owing to a plurality of equally permissible candidate meanings of “race.” Furthermore, I argue that this underdetermination leads to a deflationist diagnosis according to which disputes about the existence of human races are nonsubstantive verbal disputes. While this diagnosis resembles general deflationist strategies in contemporary metaphysics, I show that my argument does not presuppose controversial metametaphysical assumptions.

Here I explore a novel no-collapse interpretation of quantum mechanics that combines aspects of two familiar and well-developed alternatives, Bohmian mechanics and the many-worlds interpretation. Despite reproducing the empirical predictions of quantum mechanics, the theory looks surprisingly classical. All there is at the fundamental level are particles interacting via Newtonian forces. There is no wave function. However, there are many worlds.

Batterman and Rice offer an account of “minimal model explanations” and argue against “common features accounts” of those explanations. This paper offers some objections to their proposals and arguments. It argues that their proposal cannot account for the apparent explanatory asymmetry of minimal model explanations. It argues that their account threatens ultimately to collapse into a “common features account.” Finally, it argues against their motivation for thinking that an explanation appealing to “common features” would have to explain the common features’ own prevalence.