The communist norm requires that scientists widely share the results of their work. Where did this norm come from, and how does it persist? I argue on the basis of a game-theoretic model that rational credit-maximizing scientists will in many cases conform to the norm. This means that the origins and persistence of the communist norm can be explained even in the absence of a social contract or enforcement, contrary to recent work by Michael Strevens but adding to previous work emphasizing the benefits of the incentive structure created by the priority rule.

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.

Data from medical research are typically summarized with various types of outcome measures. We present three arguments in favor of absolute over relative outcome measures. The first argument is from cognitive bias: relative measures promote the reference class fallacy and the overestimation of treatment effectiveness. The second argument is decision-theoretic: absolute measures are superior to relative measures for making a decision between interventions. The third argument is causal: interpreted as measures of causal strength, absolute measures satisfy a set of desirable properties, but relative measures do not. Absolute outcome measures outperform relative measures on all counts.

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.

In many fields in the life sciences investigators refer to downward or top-down causal effects. Craver and I defended the view that such cases should be understood in terms of a constitution relation between levels in a mechanism and intralevel causal relations (occurring at any level). We did not, however, specify when entities constitute a higher-level mechanism. In this article I appeal to graph-theoretic representations of networks, now widely employed in systems biology and neuroscience, and associate mechanisms with modules that exhibit high clustering. As a result of interconnections within clusters, mechanisms often exhibit complex dynamic behaviors that constrain how individual components respond to external inputs, a central feature of top-down causation.

In this article I explore some statistical difficulties confronting going conceptions of ‘group’ as understood in accounts of group selection. Most such theories require real groups but define the reality of groups in ways that make it impossible to test for their reality. There are alternatives, but they either require or invite a nominalism about groups that many theorists abjure.

Hacking’s Law of Likelihood says—paraphrasing—that data support hypothesis H1 over hypothesis H2 whenever the likelihood ratio (LR) for H1 over H2 exceeds 1. But Hacking later noted a seemingly fatal flaw in the LR itself: it cannot be interpreted as the degree of “evidential significance” across applications. I agree with Hacking about the problem, but I do not believe the condition is incurable. I argue here that the LR can be properly calibrated with respect to the underlying evidence, and I sketch the rudiments of a methodology for so doing.

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.

Clade selection is unpopular with philosophers who otherwise accept multilevel selection theory. Clades cannot reproduce, and reproduction is widely thought necessary for evolution by natural selection, especially of complex adaptations. Using microbial evolutionary processes as heuristics, I argue contrariwise that (1) clade growth (proliferation of contained species) substitutes for clade reproduction in the evolution of complex adaptation, (2) clade-level properties favoring persistence—species richness, dispersal, divergence, and possibly intraclade cooperation—are not collapsible into species-level traits, (3) such properties can be maintained by selection on clades, and (4) clade selection extends the explanatory power of the theory of evolution.

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.

Philosophical defenses of cognitive/evolutionary psychological accounts of racialism claim that classification based on phenotypical features of humans was common historically and is evidence for a species-typical, cognitive mechanism for essentializing. They conclude that social constructionist accounts of racialism must be supplemented by cognitive/evolutionary psychology. This article argues that phenotypical classifications were uncommon historically until such classifications were socially constructed. Moreover, some philosophers equivocate between two different meanings of “racial thinking.” The article concludes that social constructionist accounts are far more robust than psychological accounts for the origins of racialism.

Newton’s earliest publications contained scandalous epistemological claims: not only did he aim for certainty; he also claimed success. Some commentators argue that Newton ultimately gave up claims of certainty in favor of a high degree of probability. I argue that no such shift occurred. I examine the evidence of a probabilistic shift: a passage from query 23/31 of the Opticks and rule 4 of the Principia. Neither passage supports a probabilistic approach to natural philosophy. The aim of certainty, then, was an enduring feature of Newton’s methodology.

Michael Weisberg and Kenneth Reisman argue that the Volterra Principle can be derived from multiple predator-prey models and that, therefore, the Volterra Principle is a prime example for robustness analysis. In the current article, I give new results regarding the Volterra Principle, extending Weisberg’s and Reisman’s work, and I discuss the consequences of these results for robustness analysis. I argue that we do not end up with multiple, independent models but rather with one general model. I identify the kind of situation in which this generalization approach may occur, and I analyze the generalized Volterra Principle from an explanatory perspective.

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.

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.

In discussion of mechanisms, philosophers often debate about whether quantitative descriptions of generalizations or qualitative descriptions of operations are explanatorily fundamental. I argue that these debates have erred by conflating the explanatory roles of generalizations and patterns. Patterns are types of variations within or between quantities in a mechanism over time or across conditions. While these patterns must often be represented in addition to descriptions of operations in order to explain a phenomenon, they are not equivalent to generalizations because their explanatory role does not depend on any specific facts about their scope or domain of invariance.

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.

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.

Evidence from cognitive science supports the claim that humans and other animals see the world as divided into objects. Although this claim is widely accepted, it remains unclear whether the mechanisms of visual reference have representational content or are directly instantiated in the functional architecture. I put forward a version of the former approach that construes object files as icons for objects. This view is consistent with the evidence that motivates the architectural account, can respond to the key arguments against representational accounts, and has explanatory advantages. I draw general lessons for the philosophy of perception and the naturalization of intentionality.

Many have suggested that the transformation standardly referred to as ‘time reversal’ in quantum theory is not deserving of the name. I argue on the contrary that the standard definition is perfectly appropriate and is indeed forced by basic considerations about the nature of time in the quantum formalism.