This article gives an explicit presentation of Newtonian gravitation on the backdrop of Maxwell space-time, giving a sense in which acceleration is relative in gravitational theory. However, caution is needed: assessing whether this is a robust or interesting sense of the relativity of acceleration depends on some subtle technical issues and on substantive philosophical questions over how to identify the space-time structure of a theory.

Traditionally, empiricism has relied on the specialness of human observation, yet science is rife with sophisticated instrumentation and techniques. The present article advances a conception of empirical evidence applicable to actual scientific practice. I argue that this conception elucidates how the results of scientific research can be repurposed across diverse epistemic contexts: it helps to make sense of how evidence accumulates across theory change, how different evidence can be amalgamated and used jointly, and how the same evidence can be used to constrain competing theories in the service of breaking local underdetermination.

Mathematicians, physicists, and philosophers of physics often look to the symmetries of an object for insight into the structure and constitution of the object. My aim in this article is to explain why this practice is successful. In order to do so, I present a collection of results that are closely related to (and, in a sense, generalizations of) Beth’s and Svenonius’s theorems.

While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to explore broad conditions under which (approximately) Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics.

The new field of meta-research investigates industry bias, publication bias, contradictions between studies, and other trends in medical research. I argue that its findings should be used as meta-evidence for evaluating therapies. ‘Meta-evidence’ is evidence about the support that direct ‘first-order evidence’ provides the hypothesis. I consider three objections to my proposal: the irrelevance objection, the screening-off objection, and the underdetermination objection. I argue that meta-research evidence works by rationally revising our confidence in first-order evidence and, consequently, in the hypothesis—typically, downward.

Philosophers sometimes claim that economics, and the idealizing strategies it employs, is ultimately unable to provide genuine laws of nature. Therefore, unlike physics, it does not qualify as an actual science. Careful consideration of thermodynamics, a well-developed physical theory, reveals substantial parallels with economic methodology. The corrective account of scientific understanding I offer appreciates these parallels: understanding in terms of efficient performance.

Influential classical and recent approaches to explicate confirmation, explanation, or explanatory power define these relations or degrees between hypotheses and evidence. This holds for both deductive and Bayesian approaches. However, this neglects the role of data, which for many everyday and scientific examples cannot simply be classified as evidence. I present arguments to sharply distinguish data from evidence in Bayesian approaches. Taking into account this distinction, we can rewrite Schupbach and Sprenger’s measure of explanatory power and show the strengths of this adaptation by applying it to the example of the detection of gravitational waves in physics.

What must laypersons understand about science to allow them to make sound decisions on science-related issues? Relying on recent developments in social epistemology, this article argues that scientific education should have the goal not of bringing laypersons’ understanding of science closer to that of expert insiders but rather of cultivating the kind of competence characteristic of “competent outsiders.” Moreover, it argues that philosophers of science have an important role to play in attempts to promote this kind of understanding but that, to successfully fulfill this role, they will have to approach central questions in the field differently.

In this article, I examine the relationship between physical quantities and physical states in quantum theories. I argue against the claim made by Arageorgis that the approach to interpreting quantum theories known as Algebraic Imperialism allows for “too many states.” I prove a result establishing that the Algebraic Imperialist has very general resources that she can employ to change her abstract algebra of quantities in order to rule out unphysical states.

Recently, Lisa Feldman Barrett and colleagues have introduced the Theory of Constructed Emotions (TCE), in which emotions are constituted by a process of categorizing the self as being in an emotional state. The view, however, has several counterintuitive implications: for instance, a person can have multiple distinct emotions at once. Further, the TCE concludes that emotions are constitutively social phenomena. In this article, I explicate the TCE*, which, while substantially similar to the TCE, makes several distinct claims aimed at avoiding the counterintuitive implications plaguing the TCE. Further, because of the changes that comprise the TCE*, emotions are not constitutively social phenomena.

The ontic conception of explanation, according to which explanations are full-bodied things in the world, is fundamentally misguided. I argue instead for what I call the eikonic conception, according to which explanations are the product of an epistemic activity involving representations of the phenomena to be explained. What is explained in the first instance is a particular conceptualization of the explanandum phenomenon, contextualized within a given research program or explanatory project. I conclude that this eikonic conception has a number of benefits, including making better sense of scientific practice and allowing for the full range of normative constraints on explanation.

Recent years have witnessed an effort to explicate the concept of explanatory power in a Bayesian framework by constructing explanatory measures. It has been argued that those measures should not violate the principle of explanatory justice, which states that explanatory power cannot be extended “for free.” I argue, by formal means, that one recent measure claiming to be immune from explanatory injustice fails to be so. I end by concluding that the explanatory justice criticism can be dissolved, given a natural interpretation of the concept of negative explanatory power.

In this article, I evaluate Hartmann and Fitelson’s solution to the Bayesian problem of old evidence by applying it to an early stage in the development of quantum theory. I argue that this case study suggests that whether old evidence is anomalous affects its support for a hypothesis. I introduce and defend two formal assumptions to accommodate this idea. This analysis not only explicates an important historical example, but it also shows that the given solution captures the intuitive importance of “surprising” evidence that has previously been problematic in the context of old evidence.

This article develops an axiomatic theory of induction that speaks to the recent debate on Bayesian orgulity. It shows the exact principles associated with the belief that data can corroborate universal laws. We identify two types of disbelief about induction: skepticism that the existence of universal laws of nature can be determined empirically, and skepticism that the true law of nature, if it exists, can be successfully identified. We formalize and characterize these two dispositions toward induction by introducing novel axioms for subjective probabilities. We also relate these dispositions to the (controversial) axiom of σ-additivity.

Daniel M. Hausman holds that preferences in economics are total subjective comparative evaluations—subjective judgments to the effect that something is better than something else all things told—and that economists are right to employ this conception of preference. Here, I argue against both parts of Hausman’s thesis. The failure of Hausman’s account, I continue, reflects a deeper problem, that is, that preferences in economics do not need an explicit definition of the kind that he seeks. Nonetheless, Hausman’s labors were not in vain: his accomplishment is that he has articulated a useful model of the theory.

Proponents of IBE claim that the ability of a hypothesis to explain a range of phenomena in a unifying way contributes to the hypothesis’s credibility in light of these phenomena. I propose a Bayesian justification of this claim that reveals a hitherto unnoticed role for explanatory unification in evaluating the plausibility of a hypothesis: considerations of explanatory unification enter into the determination of a hypothesis’s prior by affecting its ‘explanatory coherence’, that is, the extent to which the hypothesis offers mutually cohesive explanations of various phenomena.

In this article, I offer a partial analysis of the role of values in qualitative data collection in social research. The partial analysis shows that nonepistemic values have both required and permissible roles to play during this phase of research. By appeal to the analysis, I reject the ideal of value-free science as applied to qualitative data collection, and I demonstrate why two alternative ideals should likewise be dismissed as standards for values in qualitative data collection. Also, I briefly discuss the extent to which the partial analysis carries over to quantitative data collection in social research.

A pluralist about explanation posits many explanatory relevance relations, while an invariantist denies any substantial role for context in fixing genuine explanation. This article summarizes one approach to combining pluralism and invariantism that emphasizes the contrastive nature of explanation. If explanations always take contrasts as their objects and contrasts come in types, then the role for the context in which an explanation is given can be minimized. This approach is illustrated using a classic debate between natural theology and natural selection about the structure of bees’ honeycombs.

This article analyzes the antireductionist argument from renormalization group explanations of universality and shows how it can be rebutted if one assumes that the explanation in question is captured by the counterfactual dependence account of explanation.