Sober develops an account of adaptations on which they must have been positive causal factors for reproductive success. Glymour defends an account of a proper subset of adaptations—adaptations to particular environmental conditions—on which traits must interact in a special way with adapting conditions to cause reproductive success. These theories render conflicting judgments about which traits count as adaptations in some interesting cases. In this article I explore one such case and argue that we ought to replace the notion of adaptation qua positive causal factor with a novel notion of adaptation.

A high heritability estimate usually corresponds to a situation in which trait variation is largely caused by genetic variation. However, in some cases of gene-environment covariance, causal intuitions about the sources of trait difference can vary, leading experts to disagree as to how the heritability estimate should be interpreted. We argue that the source of contention for these cases is an inconsistency in the interpretation of the concepts ‘genotype’, ‘phenotype’, and ‘environment’. We propose an interpretation of these terms under which trait variance initially caused by genetic variance is subsumed into a heritability for all cases of gene-environment covariance.

Most attempts to define culture as used in the cultural evolution literature treat culture as a single phenomenon that can be given a single nondisjunctive definition. In this article I argue that, really, cultural evolutionists employ a variety of distinct but closely related concepts of culture. I show how the main prominent attempts to define a culture concept fail to properly capture all the uses of “culture” employed in cultural evolutionary work. I offer a description of some of the most important culture concepts used by cultural evolutionists.

We explore the grammar of Bayesian confirmation by focusing on some likelihood principles, including the Weak Law of Likelihood. We show that none of the likelihood principles proposed so far is satisfied by all incremental measures of confirmation, and we argue that some of these measures indeed obey new, prima facie strange, antilikelihood principles. To prove this, we introduce a new measure that violates the Weak Law of Likelihood while satisfying a strong antilikelihood condition. We conclude by hinting at some relevant links between the likelihood principles considered here and other properties of Bayesian confirmation recently explored in the literature.

Proposals for rigorously explicating the concept of confirmation in probabilistic terms abound. To foster discussions on the formal properties of the proposed measures, recent years have seen the upshot of a number of representation theorems that uniquely determine a confirmation measure (up to ordinal equivalence) based on a number of desiderata. However, the results that have been presented so far focus exclusively on the concept of incremental confirmation. This leaves open the question whether similar results can be obtained for the concept of absolute confirmation. This article closes the gap by providing a representation theorem for absolute confirmation measures.

There are two senses in which a hypothesis may be said to unify evidence: (1) ability to increase the mutual information of a set of evidence statements; (2) explanation of commonalities in phenomena by positing a common origin. On Bayesian updating, only Mutual Information Unification contributes to incremental support. Defenders of explanation as a confirmatory virtue that makes independent contribution must appeal to some relevant difference between humans and Bayesian agents. I argue that common origin unification has at best a limited heuristic role in confirmation. Finally, Reichenbachian common cause hypotheses are shown to be instances of Mutual Information Unification.

Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomenon and little understanding of underlying mechanics. A first problem, we argue, is that polarization appears in the literature as not one concept but many. In the first part of the article, we distinguish nine phenomena that may be considered polarization, with suggestions of appropriate measures for each. In the second part of the article, we apply this analysis to evaluate the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization.

This article motivates a shift in certain strands of the debate over legitimate roles for nonepistemic values in scientific practice from investigating what is involved in taking cognitive attitudes like acceptance toward an empirical hypothesis to looking at a social understanding of assertion, the act of communicating that hypothesis. I argue that speech act theory’s account of assertion as a type of doing makes salient legitimate roles nonepistemic values can play in scientific practice. The article also shows how speech act theory might provide a framework for fruitfully extending aspects of the social and pragmatic turns in the philosophy of science.