This article argues against general claims for the epistemic superiority of experiment over observation. It does so by dissociating the benefits traditionally attributed to experiment from physical manipulation. In place of manipulation, we argue that other features of research methods do confer epistemic advantages in comparison to methods in which they are diminished. These features better track the epistemic successes and failures of scientific research, crosscut the observation/experiment distinction, and nevertheless explain why manipulative experiments are successful when they are.

Bayesian agents, argues Belot, are orgulous: they believe in inductive success even when guaranteed to fail on a topologically typical collection of data streams. Here we shed light on how pervasive this phenomenon is. We identify several classes of inductive problems for which Bayesian convergence to the truth is topologically typical. However, we also show that, for all sufficiently complex classes, there are inductive problems for which convergence is topologically atypical. Last, we identify specific topologically typical collections of data streams, observing which guarantees convergence to the truth across all problems from certain natural classes of effective inductive problems.

Many philosophers sympathetic with Humeanism about laws have thought that the fundamental laws will include not only the traditional dynamical equations, but also two additional principles: the Past Hypothesis (PH) and the Statistical Postulate (SP). PH says that the universe began in a particular very-low-entropy macrostate M(0), and SP posits a uniform probability distribution over the microstates compatible with M(0). This view is arguably vindicated by the orthodox Humean Best System Account (BSA). However, I argue that recent developments of the BSA render the Past Hypothesis otiose. In particular, Pragmatic Humeanism does not support the idea that PH is a law.

In light of recent criticisms by Woodward (2017) and Rescorla (2018), we examine the relationship between mechanistic explanation and phenomenological laws. We disambiguate several uses of the phrase “phenomenological law” and show how a mechanistic theory of explanation sorts them into those that are and are not explanatory. We also distinguish the problem of phenomenological laws from arguments about the explanatory power of purely phenomenal models, showing that Woodward and Rescorla conflate these problems. Finally, we argue that the temptation to pit mechanistic and interventionist theories of explanation against one another occludes important and scientifically relevant research questions.

Scientists may sometimes generalize from their samples to broader populations when they have not yet sufficiently supported this generalization. Do such hasty generalizations also occur in experimental philosophy? To check, we analyzed 171 experimental philosophy studies published between 2017 and 2023. We found that most studies tested only Western populations but generalized beyond them without justification. There was also no evidence that studies with broader conclusions had larger, more diverse samples, but they nonetheless had higher citation impact. Our analyses reveal important methodological limitations of many experimental philosophy studies and suggest that philosophical training may not protect against hasty generalizations.

The central role of such epistemic concepts as theory, explanation, model, or mechanism is rarely questioned in philosophy of science. Yet, what is their actual use in the practice of science? Here, we deploy text-mining methods to investigate the usage of 61 epistemic notions in a corpus of full-text articles from the biological and biomedical sciences (N = 73,771). The influence of disciplinary context is also examined by splitting the corpus into subdisciplinary clusters. The results reveal the intricate semantic networks that these concepts actually form in the scientific discourse, not always following our intuitions, at least in some parts of science.

Basal cognition investigates cognition working upward from nonneuronal organisms. Because basal cognition is committed to empirically testable hypotheses, a methodological challenge arises: how can experiments avoid using zoocentric assumptions that ignore the ecological contexts that might elicit cognitively driven behavior in nonneuronal organisms? To meet this challenge, I articulate the principle of dynamic holism (PDH), a methodological principle for guiding research on nonneuronal cognition. I describe PDH’s relation to holistic research programs in human-focused cognitive science and psychology then present an argument from analogy based on holistic developmental biology. Last, I examine two experiments exemplifying the need for PDH.

Modal relationism is the view that our best physical theories can dispense with substantival space or spacetime in favor of possible configurations of particles. Kenneth Manders argues that the substantivalist conception is equivalent to this Leibnizian conception of space. To do so, Manders provides a translation $f$ from the Newtonian theory ${T_N}$ into the Leibnizian modal relationist account ${T_L}$. In this article, we show that the translation does not establish equivalence because there is no translation $g:{T_L} \mapsto {T_N}$ that preserves theoremhood. This seems to show that the modal relationist theory ${T_L}$ is less parsimonious than its substantivalist rival.

Traditionally, the debate about health and disease is characterized as an opposition between naturalism and normativism. However, recent contributions show that theories of health and disease need not be purely naturalistic or normative but may be located somewhere in between. The first purpose of this article is to further advance this line of nuancing. The second purpose is to argue in favor of a specific position, which the added nuances reveal. I call this position subjectively salient naturalism. If one is interested in scientific concepts of health and disease, subjectively salient naturalism is a more plausible position than naturalism.

Cognitive representations are typically analyzed in terms of content, vehicle, and format. Although current work on formats appeals to intuitions about external representations, such as words and maps, in this article, we develop a computational view of formats that does not rely on intuitions. In our view, formats are individuated by the computational profiles of vehicles, that is, the set of constraints that fix the computational transformations vehicles can undergo. The resulting picture is strongly pluralistic, makes space for a variety of different formats, and is intimately tied to the computational approach to cognition in cognitive science and artificial intelligence.

Epistemic uncertainties are included in probabilistic risk assessment (PRA) as second-order probabilities that represent the degrees of belief of the scientists that a model is correct. In this article, I propose an alternative approach that incorporates the scientist’s confidence in a probability set for a given quantity. First, I give some arguments against the use of precise probabilities to estimate scientific uncertainty in risk analysis. I then extend the “confidence approach” developed by Brian Hill and Richard Bradley to PRA. Finally, I claim that this approach represents model uncertainty better than the standard (Bayesian) model does.

Historians have shown that philosophical discussions about the implications of relativity significantly shaped the development of European philosophy of science in the 1920s. Yet little is known about American debates from this period. This article maps the first responses to Einstein’s theory in three U.S. philosophy journals and situates these papers within the local intellectual landscape. I argue that these discussions (1) stimulated the development of a distinctly American branch of philosophy of science and (2) paved the way for the logical empiricists who emigrated to the United States in the years before World War II.

We model the impact of different incentives on journal behavior in undertaking peer review. Under one scheme, the journal aims to publish the highest-quality papers; under the second, the journal aims to maintain a high rejection rate. Under both schemes, journals prefer to set very high standards for acceptance despite allowing significant error in peer review. Under the second scheme, however, in order to encourage more submissions of mediocre papers, the journal is incentivized to make its editorial process less accurate. This leads to both worse peer review and lower-quality articles being published.

We provide five rearticulations of the thesis that the structure of spacetime is conventional, rather than empirically determined, based upon variation of the structures that are empirically underdetermined and modal contexts in which this underdetermination occurs. Three of the five formulations of conventionalism will be found to fail. Two are found to open up new interesting problems for researchers in the foundations of general relativity. In all five cases, our analysis explores the interplay between geometric identities, symmetry, conformal structure, and the dynamical content of physical theories with the conventionalism dialectic deployed as a tool of explication, clarification, and exploration.

Recent developments in generalized probability theory have renewed a debate about whether regularity (i.e., the constraint that only logical contradictions get assigned probability $0$) should be a necessary feature of both chances and credences. Crucial to this debate, however, are some mathematical facts regarding the interplay between the existence of regular generalized probability measures and various cardinality assumptions. We improve on several known results in the literature regarding the existence of regular generalized probability measures. In particular, we give necessary and sufficient conditions for the existence of regular generalized probability measures defined on the whole powerset of any sample space.

Behavioral welfare economics usually aims at mere means paternalism, helping agents better pursue their own goals. This paper discusses one initially promising way to inform policies addressed at agents who violate expected utility theory (EUT), namely what I call “CPT debiasing.” I argue that this approach is problematic even if we grant the normative authority of EUT, the descriptive adequacy of CPT (cumulative prospect theory), and the general acceptability of means paternalism. First, it is doubtful whether the CPT utility function measures what its proponents intend. Second, by imposing risk neutrality on agents, the approach involves a more problematic paternalism.

Grant Ramsey and Michael Deem argue that appreciating the role that empathy plays in posttransgression guilt leads to a more promising account of the emotion’s evolutionary origins. But because their proposal fails to adequately distinguish guilt from shame, we cannot say which of the two emotions we are actually getting an evolutionary account of. Moreover, a closer look at the details suggests both that empathy may be more relevant for our understanding of shame’s evolutionary origins than guilt’s and that guilt is unlikely to be an adaptation.

We focus on a neglected aspect of scientific theory choice: how the selection of theories affects epistemic values. Building on Kuhn, we provide a general characterization of the feedback-loop dynamic between theories and values in theory choice as analogous to the relationship between organisms and the environment in niche construction. We argue that understanding theory choice as niche construction can explain how certain values acquire more weight and a specific application over time, and how resistance to scientific change can, therefore, arise. We illustrate our picture by looking at the Mendelian–biometrician controversy.

Recent work on the status of astrophysical modeling in the wake of quantum gravity indicates that a “fauxrizon” (a portmanteau of faux horizon), such as is relevant to understanding astrophysical black holes according to the fuzzball proposal within string theory, might ultimately solve the familiar black hole evaporation paradox. I clarify, with general upshots for the foundations of quantum gravity research, some of what this suggestion would amount to: identification of intertheoretic constraints on global spacetime structure in (observer-relative) semiclassical models of fuzzballs.