This article tackles the objection that revealed preferences cannot causally explain. I mount a causal explanatory defense by drawing out three conditions under which such preferences can explain well, using an example of a successful explanation employing behavioral preferences. When behavioral preferences are multiple realizable, they can causally explain behavior well. Behavioral preferences also explain when agential preferences cannot be analytically separated from the environment that produces the relevant behavior (Condition 2) and when the environment is a significant causal factor (Condition 3). Thus, there are not causal explanatory grounds to completely bar revealed preference explanations from social science.

This article concerns the diachronic rationality norms for comparative confidence judgments, that is, judgments of the form “I am at least as confident in $p$ as I am in $q$.” Specifically, it identifies, characterizes, and evaluates an intuitively compelling learning rule called comparative conditionalization that specifies how agents should revise their comparative confidence judgments in the face of novel evidence.

The modern Everett interpretation of quantum mechanics describes an emergent multiverse. The goal of this paper is to provide a perspicuous characterisation of how the multiverse emerges making use of a recent account of (weak) ontological emergence. This will be cashed out with a case study that identifies decoherence as the mechanism for emergence. The greater metaphysical clarity enables the rebuttal of critiques due to Baker (2007) and Dawid and Thébault (2015) that cast the emergent multiverse ontology as incoherent; responses are also offered to challenges to the Everettian approach from Maudlin (2010) and Monton (2013).

There is a Dutch Book argument for the axiom of countable additivity for subjective probability functions, but de Finetti famously rejected the axiom, arguing that it wrongly renders a uniform distribution impermissible over a countably infinite lottery. Dubins however showed that rejecting countable additivity has a strongly paradoxical consequence that a much weaker rule than countable additivity blocks. I argue that this rule, which also prohibits the de Finetti lottery, has powerful independent support in a desirable closure principle. I leave it as an open question whether countable additivity should be adopted.

I develop a novel account of how nonepistemic aims and values can appropriately influence scientific investigation. At its heart is a process of epistemic projection in which a nonepistemic aim or value is mapped to an epistemic research problem that aligns with that aim or value. Choices in research are then justified as a means of solving that research problem. This epistemic projection approach makes research responsive to nonepistemic aims and values yet remains consistent with the value-free ideal; it could be acceptable to parties on both sides of the values-in-science debate. It also promises to be useful in practice.

I defend a novel account of scientific progress centered around justification. Science progresses, on this account, where there is a change in justification. I consider three options for explicating this notion of change-in-justification. This account of scientific progress dispels with a condition for scientific progress that requires accumulation of truth or truth-likeness, and it emphasizes the social nature of scientific justification.

Sexes are normally taken to be fundamental categories in biology—many sexually reproducing organisms fall under the categories of female/male. Much research aims at explaining differences between sexes. Sexual selection forms a central framework for explaining “typical” distributions of traits among sexes and explicating circumstances leading to “reversal.” I claim that sexual selection models need not make use of sexes and that sexes lack explanatory significance in such models. I offer a framework of reproductive dimorphism and argue that it is better than that of sexes because it (1) is more compatible with explanations of sexual selection and (2) allows for their greater applicability.

In a conventional experiment, scientists typically aim to learn about target systems by manipulating source systems of the same material type. In an analogue quantum simulation, by contrast, scientists typically aim to learn about target quantum systems of one material type via an experiment on a source quantum system of a different material type. In this article, we argue that such inferences can be justified by reference to source and target quantum systems being of the same empirical type. We illustrate this novel experimental practice of wavefunction engineering with reference to the example of Bose–Hubbard systems.

Teleosemantic theories aim to naturalize mental representation through the use of functions, typically based on past selection processes. However, the historical dependence of these theories has faced severe criticism, leading some philosophers to develop ahistorical alternatives. This article presents a new dilemma for all ahistorical teleosemantic theories, focusing in particular on the theories proposed by Timothy Schroeder and Bence Nanay. These theories require certain dispositions in the producers or consumers of mental representations, but the appeal to dispositions puts the proponents in an undesirable position: mental content is either overly dependent on current circumstances or ultimately dependent on historical factors.

Confirmation bias has been widely studied for its role in failures of reasoning. Individuals exhibiting confirmation bias fail to engage with information that contradicts their current beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. We use network models to show that moderate confirmation bias often improves group learning. However, a downside is that a stronger form of confirmation bias can hurt the knowledge-producing capacity of the community.

We challenge the standard interpretation of pain asymbolia (PA), a neuropsychiatric condition that causes unusual reactions to pain stimuli. The standard interpretation asserts that PA subjects experience pain but lack important features of the experience. However, we argue that the clinical evidence for PA does not support this interpretation and that the arguments put forward by the defenders of the standard interpretation end up making self-contradicting claims. Finally, we suggest that the best interpretation of the available evidence is to take a deflationist stance toward PA, at least until further evidence becomes available.

Some scientific models and some claims about model–target relations are fruitfully diagnosed as dogwhistles. Dogwhistles, broadly speaking, are speech acts that send different, conflicting, and often differentially inflammatory messages to listeners. I distinguish two ways in which scientific models can be dogwhistles: representational dogwhistling and fit-for-purpose dogwhistling. I illustrate both kinds of dogwhistling using an example from computational social science, the diversity trumps ability theorem. I argue that dogwhistling threatens the objectivity of science, and I propose some ameliorative strategies.

Two types of formal models—landscape search tasks and two-armed bandit models—are often used to study the effects that various social factors have on epistemic performance. I argue that they can be understood within a single framework. In this unified framework, I develop a model that may be used to understand the effects of functional and demographic diversity and their interaction. Using the unified model, I find that the benefit of demographic diversity is most pronounced in a functionally homogeneous group, and decreases with increasing functional diversity.

Standard narratives about physical teleology say its death was a fait accompli of the Scientific Revolution, but the principle of least action (PLA) has been taken to instantiate teleology’s survival into Enlightenment physics. Other scholars claim this PLA-based teleological metaphysics fell to general philosophical attacks on final causes. None of these narratives fully captures the philosophical interest of its demise. It illustrates a metaphysics being refuted because it could not be coherently modeled in mathematics, hence directly through mathematization and not by philosophical argument or empirical test.

Our thinking often uses rich memories of particular past events. Yet frequently we would do better to use other forms of memory. I show that existing accounts of the function of episodic memory cannot account for such cases, then develop an account which can. Roughly: rich representations of particular past events are required for Unrestricted Learning, learning which is not limited in how much of the world’s complexity it can capture; and episodic memory’s selection for Unrestricted Learning could explain its ubiquitous (and often inappropriate) use for other tasks. This proposal suggests many avenues for further empirical and computational research.

What is the nature of deception? What does it take for an organism to deceive another one? In this article we address these questions by appealing to the concept of mimicry. More precisely, we argue that a fruitful perspective regards deception as an instance of mimicry rather than the reverse. Conceiving of deception as an instance of mimicry has a number of interesting consequences: It draws connections between different areas of research, vindicates a functional approach to deception by providing a satisfactory answer to some recent objections, and suggests some worries for game-theoretic approaches to deception.

Among advocates and critics of the “extended evolutionary synthesis” (EES), “reciprocal causation” refers to the view that adaptive evolution is a bidirectional phenomenon, whereby organisms and environments impinge on each other through processes of niche construction and natural selection. I argue that reciprocal causation is incompatible with the view that natural selection is a metaphysically emergent causal process. The emergent character of selection places reciprocal causation on the horns of dilemma, and neither horn can rescue it. I conclude that proponents of the EES must abandon the claim that the process of natural selection features in cycles of reciprocal causation.

Scientists and philosophers alike debate whether various systems such as plants and bacteria exercise cognition. One strategy for resolving such debates is to ground claims about nonhuman cognition in evidence from mathematical models of cognitive capacities. In this article, I show that proponents of this strategy face two major challenges: demarcating phenomenological models from process models and overcoming underdetermination by model fit. I argue that even if the demarcation problem is resolved, fitting a process model to behavioral data is, on its own, not strong evidence for any cognitive process, let alone processes shared with humans.

Psychology is a discipline that has a high number of failed replications, which has been characterized as a “crisis” on the assumption that failed replications are indicative of untrustworthy research. This article uses Chang’s concept of epistemic iteration to show how a research program can advance epistemic goals despite many failed replications. It illustrates this by analyzing an ongoing large-scale replication attempt of Southgate et al.’s work exploring infants’ understanding of false beliefs. It concludes that epistemic iteration offers a way of understanding the value of replications—both failed and successful—that contradicts the narrative centered around distrust.