According to Michael Friedman’s theory of explanation, a law X explains laws Y1, Y2, …, Yn precisely when X unifies the Y’s, where unification is understood in terms of reducing the number of independently acceptable laws. Philip Kitcher criticized Friedman’s theory but did not analyze the concept of independent acceptability. Here we show that Kitcher’s objection can be met by modifying an element in Friedman’s account. In addition, we argue that there are serious objections to the use that Friedman makes of the concept of independent acceptability.

Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence (OI)—when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a sufficient independence condition for warranting robustness arguments. We show that OI evidence can collectively confirm a hypothesis to a lower degree than individual lines of evidence, contrary to the standard assumption undergirding usual robustness arguments. We employ Bayesian networks to represent the ideal empirical scenario for a robustness argument and a variety of ways in which empirical scenarios can fall short of this ideal.

A certain type of counterfactual is thought to be intimately related to causation, control, and explanation. The time asymmetry of these phenomena therefore plausibly arises from a time asymmetry of counterfactual dependence. But why is counterfactual dependence time asymmetric? The most influential account of the time asymmetry of counterfactual dependence is David Albert’s account, which posits a new, time-asymmetric fundamental physical law, the so-called past hypothesis. Albert argues that the time asymmetry of counterfactual dependence arises from holding fixed the past hypothesis when evaluating counterfactuals. In this article, I argue that Albert’s account misconstrues the time asymmetry of counterfactual dependence.

This article suggests a revision of the theory of causal nets (TCN). In section 1 we introduce an axiomatization of TCN based on a realistic understanding. It is shown that the causal Markov condition entails three independent principles. In section 2 we analyze indeterministic decay as the major counterexample to one of these principles: screening off by common causes (SCC). We call SCC-violating common causes interactive causes. In section 3 we develop a revised version of TCN, called TCN*, which accounts for interactive causes. It is shown that there are interactive causal models that admit of no faithful noninteractive reconstruction.

I argue that there are such things as nomological probabilities—probabilities that play a certain explanatory role with respect to stable, long-run relative frequencies. Indeed, I argue, we should be willing to accept nomological probabilities even if they turn out to be metaphysically weird or even wholly sui generis entities. I then give an example of one way in which this argument should shape future work on the metaphysics of chance by describing a challenge to a common group of analyses of objective probability—Humean analyses—understood as analyses of nomological probability.

The Intergovernmental Panel on Climate Change has developed a novel framework for assessing and communicating uncertainty in the findings published in its periodic assessment reports. But how should these uncertainty assessments inform decisions? We take a formal decision-making perspective to investigate how scientific input formulated in the IPCC’s novel framework might inform decisions in a principled way through a normative decision model.

I present and defend the generalized selected effects (GSE) theory of function. According to GSE, the function of a trait consists in the activity that contributed to its bearer’s differential reproduction, or differential retention, within a population. Unlike the traditional selected effects (SE) theory, it does not require that the functional trait helped its bearer reproduce; differential retention is enough. Although the core theory has been presented previously, I go significantly beyond those presentations by providing a new argument for GSE and defending it from a recent objection. I also sketch its implications for teleosemantics and philosophy of medicine.

Standard applications of evolutionary game theory look at a single game and focus on the evolution of behavior for that game alone. Instead, this article uses tools from evolutionary game theory to study the competition between choice mechanisms in a rich and variable multigame environment. A choice mechanism is a way of subjectively representing a decision situation, paired with a method for choosing an act based on this subjective representation. We demonstrate the usefulness of this approach by a case study that shows how subjective representations in terms of regret that differ from the actual fitness can be evolutionarily advantageous.

Paul Griffiths et al. have proposed a quantitative measure of causal specificity and used it to assess various attempts to single out genetic causes as being causally more specific than other cellular mechanisms, for example, alternative splicing. Focusing in particular on developmental processes, they have identified a number of important challenges for this project. In this discussion note, I would like to show how these challenges can be met.