This article defends a version of the Westermarck Effect, integrating existing clinical, biological, and philosophical dimensions to incest avoidance. By focusing on care-based attachment in primates, my formulation of the effect suggests the power of a phylogenetic argument widely accepted by primatologists but not by cultural anthropologists. Identifying postadoption incest as a phenomenon with underexplored evidential value, the article sketches an explanatory strategy for reconciling the effect with the clinical reality of incest, concluding with an explicit argument against culture-first or conventionalist accounts of incest avoidance prevalent in anthropology.

This article defends the Negative View of natural selection explanation, according to which natural selection cannot explain of any given individual why it has the traits it does. Over the years, this view has been criticized on empirical, metaphysical, and explanatory grounds. I review the debate and offer additional reasons for rejecting the empirical and metaphysical objections. The explanatory objection, which holds that the Negative View is rooted in a flawed account of contrastive explanation, initially seems plausible. However, I argue that a closer consideration of the desiderata of contrastive explanation shows that this objection fails as well.

I analyze a tension at the core of the mechanistic view of computation generated by its joint commitment to the medium independence of computational vehicles and to computational systems possessing teleological functions to compute. While computation is individuated in medium-independent terms, teleology is sensitive to the constitutive physical properties of vehicles. This tension spells trouble for the mechanistic view, suggesting that there can be no teleological functions to compute. I argue that, once considerations about the relevant function-bestowing factors for computational systems are brought to bear, the tension dissolves: physical systems can have the teleological function to compute.

The life sciences are said to be in the midst of a replication crisis because (1) a majority of published results are irreproducible, and (2) scientists rarely replicate existing data. Here I argue that point 2 of this assessment is flawed because there is a hitherto unidentified form of replication in the experimental life sciences, which I call ‘microreplications’ (MRs). Using a case study from biochemistry, I illustrate how MRs depend on a key element of experimentation, namely, experimental controls. I end by reflecting on what MRs mean for the broader debate about the replication crisis.

To systematically answer the generalized Kretschmann objection, I propose a mean to make operational a criterion widely recognized as allowing one to decide whether the gauge symmetry of a theory is artificial or substantial. My proposition is based on the dressing field method of gauge symmetry reduction, a new simple tool from mathematical physics. This general scheme allows one in particular to straightforwardly argue that the notion of spontaneous symmetry breaking is superfluous to the empirical success of the electroweak theory. Important questions regarding the context of justification of the theory then arise.

The replicator dynamics and Moran process are the main deterministic and stochastic models of evolutionary game theory. The models are connected by a mean-field relationship—the former describes the expected behavior of the latter. However, there are conditions under which their predictions diverge. I demonstrate that the divergence between their predictions is a function of standard techniques used in their analysis and of differences in the idealizations involved in each. My analysis reveals problems for stochastic stability analysis in a broad class of games, demonstrates a novel domain of agreement between the dynamics, and indicates a broader moral for evolutionary modeling.

I propose a general alethic theory of epistemic risk according to which the riskiness of an agent’s credence function encodes her relative sensitivity to different types of graded error. After motivating and mathematically developing this approach, I show that the epistemic risk function is a scaled reflection of expected inaccuracy (a quantity also known as generalized information entropy). This duality between risk and information enables us to explore the relationship between attitudes to epistemic risk, the choice of scoring rules in epistemic utility theory, and the selection of priors in Bayesian epistemology more generally (including the Laplacean principle of indifference).

This article contributes to the underdeveloped field of experimental philosophy of science. We examine variability in the philosophical views of scientists. Using data from Toolbox Dialogue Initiative, we analyze scientists’ responses to prompts on philosophical issues (methodology, confirmation, values, reality, reductionism, and motivation for scientific research) to assess variance in the philosophical views of physical scientists, life scientists, and social and behavioral scientists. We find six prompts about which differences arose, with several more that look promising for future research. We then evaluate the difference between the natural and social sciences and the challenge of interdisciplinary integration across scientific branches.