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.

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.

Piccinini’s usability constraint states that physical processes must have “physically constructible manifestation[s]” to be included in epistemically useful models of physical computation. But to determine what physical processes can be implemented in physical systems (as parts of computations), we must already know what physical processes can be implemented in physical systems (as parts of processes for constructing computing systems). We need additional assumptions about what qualifies as a building process. Piccinini implicitly assumes a classical computational understanding of executable processes, but this is an assumption imposed on physical theories and may artificially limit our picture of epistemically useful physical computation.

I discuss a contemporary solution to the dynamic problem of old evidence (POE), as proposed by Sprenger. Sprenger’s solution combines the Garber–Jeffrey–Niiniluoto (GJN) approach with Howson’s suggestion of counterfactually removing the old evidence from scientists’ belief systems. I argue that in the dynamic POE, the challenge is to explain how an insight under beliefs in which the old evidence E is known increased the credence of a scientific hypothesis. Therefore, Sprenger’s counterfactual solution, in which E has been artificially removed, does not resolve the problem. I consider several potential responses.

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.

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.

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.

Scientific disagreements are an important catalyst for scientific progress. But what happens when scientists disagree amid times of crisis, when we need quick yet reliable policy guidance? In this article, we provide a normative account for how scientists facing disagreement in the context of “fast science” should respond and how policy makers should evaluate such disagreement. Starting from an argumentative, pragma-dialectic account of scientific controversies, we argue for the importance of higher-order evidence (HOE), and we specify desiderata for scientifically relevant HOE. We use our account to analyze the controversy about the aerosol transmission of COVID-19.

Howson (2000) contends that the No-Miracles argument fails as an argument in support of scientific realism because it commits the base-rate fallacy. Psillos (2009) has defended the argument by appealing to cases that involve conditional probabilities but where base-rate information can properly be ignored. I show that Psillos’s defense of the No-Miracles argument is inadequate and that the prospects for a purely probabilistic formulation of the argument are dim. I end by considering whether interpreting the argument as an inference to the best explanation might better serve the scientific realist, concluding that such an approach would limit the realist’s ability to effectively counter the Pessimistic Induction.

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.

The COVID-19 global pandemic had a profound effect on scientific practice. During this time, officials crucially relied on the work done by modelers. This raises novel questions for the philosophy of science. Here I investigate the possibility of 'natural models' in predicting the SARS-Cov-2 virus’s trajectory for epidemiological purposes. I argue that to the extent that these can be considered scientific models, they support the possibility of a continuum from scientific models to natural models differing in artifactual commitment. In making my case, I draw from work on both model organisms and natural experiments as well as recent work in epidemiology.

Economists often consult multiple models in order to combat model uncertainty in the face of misspecification. By examining modeling practices at the Bank of England, this paper identifies an important, but underappreciated modeling procedure. Sometimes an idealized model is manipulated to reproduce the results from another distinct auxiliary model, ones which it could not produce on its own. However, this procedure does not involve making the original model “more realistic,” insofar as this means adding in additional causal factors. This suggests that there are ways to make models more representationally adequate that do not involve de-idealization in the straightforward sense.

Inferences from clinical research results to estimates of therapeutic effectiveness suffer due to various biases. I argue that predictions of medical effectiveness are prone to failure because current medical research overlooks the impacts of a particularly detrimental set of biases: meta-biases. Meta-biases are linked to higher-level characteristics of medical research and their effects are only observed when comparing sets of studies that share certain meta-level properties. I offer a model for correcting research results based on meta-research evidence, the bias dynamics model, which employs regularly updated empirical bias coefficients to attenuate estimates of therapeutic effectiveness.

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.

I argue that the temporal asymmetry of influence is not merely the result of thermodynamics: it is a consequence of the fact that the modal structure of the universe must admit only processes that cannot give rise to contradictions. I appeal to the process matrix formalism developed in the field of quantum foundations to characterize processes that are compatible with local free will while ruling out contradictions, and I argue that this gives rise to “consistent-chaining” requirements that explain the temporal asymmetry of influence. I compare this view to the perspectival account of causation advocated by Price and Ramsey.

Current cosmological observations place little constraints on the nature of dark matter, allowing the development of a large number of models and various methods for probing their properties, which seem to provide ideal grounds for the employment of robustness arguments. In this article, the extent to which such arguments can be used to overcome various methodological and theoretical challenges is examined. The conclusion is that although robustness arguments have a limited scope in the context of dark-matter research, they can still be used to increase the scientists’ confidence about the properties of specific models.

This article draws on Kukla’s “Institutional Definition of Health” to provide a definition of “psychiatric condition” that delineates the proper bounds of psychiatry. I argue that this definition must include requirements that psychiatrization of a condition benefit the well-being of (1) the society as a collective and (2) the individual whose condition is in question. I then suggest that psychiatry understand individual well-being in terms of the subjective values of individuals. Finally, I propose that psychiatry’s understanding of collective well-being should be the result of a “socially objective” process and give certain desiderata for this understanding.

This article shows how institutional values influence the design and evaluation of arguments in funding proposals for research. We characterize a general argument made within proposals and several kinds of subarguments that contribute to it. We indicate that funders’ values inform the kinds of proposal documents funders require and their relative weighting of them. We illustrate these points by showing how a program office in the US National Oceanic and Atmospheric Administration (NOAA) uses its public service mission to require and heavily weigh arguments to transition new knowledge to NOAA service providers, and we suggest conceptual questions raised by the use of transition knowledge.

The compatibility of the Gaia hypothesis with Darwinism is often challenged on the grounds that (1) to be potent, natural selection requires the existence of a population (whereas Gaia is a single entity), and (2) natural selection requires the entities forming a population to reproduce (whereas Gaia merely persists). However, using the Price equation, I argue, following others, that the Gaia hypothesis can fit squarely within a Darwinian framework because Gaia can exhibit adaptations if a process at a lower level (e.g., an ecosystem) can occur, and the notion of natural selection can be extended to accommodate evolution without reproduction.