Philosophers have claimed that: (a) Born-Oppenheimer approximation methods for solving molecular Schrödinger equations violate the Heisenberg uncertainty relations; therefore, (b) ‘quantum chemistry’ is not fully quantum; and (c) therefore chemistry does not reduce to physics. This paper analyses the reasoning behind Born-Oppenheimer methods and shows that they are internally consistent and fully quantum mechanical, contrary to (a)-(c). Our analysis addresses important issues of mathematical rigour, physical idealization, reduction, and classicality in the quantum theory of molecules, and we propose an agenda for the philosophy of quantum chemistry more grounded in scientific practice.

Philosophers often defend appeals to parsimony by invoking its central role in science. I argue that this move fails once we distinguish between two uses of parsimony: non-ideal and ideal. Non-ideal parsimony enjoys strong inductive support in science, since complex models are prone to overfit to predictively irrelevant noise. But philosophical data aren’t significantly noisy in the relevant sense: when our intuitions are unreliable, their unreliability typically reflects systematic bias rather than noise, which parsimony doesn’t mitigate. Philosophers therefore need ideal parsimony, which finds only weak support from science. Thus, the scientific analogy cannot vindicate the philosopher’s use of parsimony.

The standard Bayesian solution to the paradox of the ravens maintains that the degree of confirmation provided by seeing a non-black non-raven is positive but negligible compared to that provided by seeing a black raven. I show that, unless we impose severe and unmotivated restrictions on the subject’s priors, this has the consequence that the cumulative confirmation provided by all the non-black non-ravens the subject expects to see is non-negligible compared to the cumulative confirmation provided by all the black ravens the subject expects to see. If this is so, however, then the paradox retains its full force.

Rerandomization is a new technique employed in randomized field experiments (RFEs) to enhance the balance of covariates across experimental groups. Rerandomization is recommended because it reduces imbalances in known covariates, thereby enhancing the precision of the average treatment effect estimates. However, employing rerandomization necessitates adjusting observed p-values, using regression-based inference, and selecting predictive covariates. All these amendments increase the number of researcher degrees of freedom, i.e., methodological decisions involved in designing and analyzing experiments. I argue that this increased analytical flexibility may be misused to p-hack for statistically significant or preferred results, thereby reducing the credibility of the results.

Some philosophers argue that pragmatist accounts of causation require accepting perspectivalism—the view that causation depends on an agent’s perspective. This paper critically evaluates this inference by examining Price’s arguments for perspectivalism and against Woodward’s view. I demonstrate that Price’s positive argument rests on an unacceptable premise, and drawing on Woodward’s work, I propose a pragmatist realist view of causation that survives Price’s criticisms. This pragmatist realism identifies causes through human concerns and practices, but treats the causal relation as objective and independent of agential perspectives. The paper concludes by showing Ismael’s perspectivalist view is consistent with pragmatist realism.

Evolutionary game-theoretic (EGT) models of morality face powerful under-addressed objections. Critics claim the simulations fail to specify their explanandum, muddying their explanatory value. Additionally, morality is suggested to be not computationally representable, jeopardising the method’s general applicability. This paper explicates and addresses the objections. I argue at least one concrete explication of morality, emotionism coupled with functionally understood emotions, can be a plausible subject of EGT explanations. I demonstrate how fixing this explanandum assuages the methodological objections and provide a computational model as proof of concept. If successful, the contribution placates serious long-standing criticisms of EGT as a meta-ethical tool.

Strategic science skeptics criticize scientific claims solely to promote non-epistemic goals. I will analyze and debunk a philosophically neglected argument exploited by strategic science skeptics: the argument from disagreement. The core of this argument is that one should lower one’s confidence in a scientific claim when having learned that there is a scientific disagreement about this claim. I will develop a (Bayesian) Justificatory Account of Multiple Testimony to provide a normative characterization of how learning about agreements and disagreements is connected to confirming and disconfirming scientific claims. I will use this account to debunk the argument from disagreement.

Abstract

This paper introduces a novel framework for causal selection based on an analysis of different ways in which causes interact. Some causal interactions function to enable the operation of a mechanism, while others modify the behavior or outcome of that mechanism, allowing fine-grained descriptions of causal relationships. Distinguishing between enabling and modifying makes it possible to separate distinct causal functions that are wrongly grouped into an undifferentiated category of background conditions. Drawing on case studies from ecology, the framework offers new insights into why some factors should be cited in explanations while others remain implicit, despite being causally indispensable.

Teleological explanations are those that explain a phenomenon in virtue of a consequence it brings about. This has long been challenged on the grounds that it invokes backward causation. The classic resolution to this is to show that these consequences explain as causes which occurred in the past. An alternative characterizes teleology as a form of non-causal explanation. Against the widespread assumption that teleological explanations are univocal, I argue that causal and non-causal variants are compatible insofar as they explain different aspects of the same purposive phenomena. I conclude that we ought to be pluralists about teleological explanation.

Goldman (2001) asks how novices can trust putative experts when background knowledge is scarce. We develop a reinforcement-learning model, adapted from Barrett, Skyrms, and Mohseni (2019), in which trust arises from experience rather than prior expertise labels. Agents incrementally weight peers who outperform them. Using a large dataset of human probability judgments as inputs, we simulate communities that learn whom to defer to. Both a strictly individual-learning variant and a reputation-sharing variant yield performance-sensitive deference, the latter accelerating convergence. Our results offer an empirically grounded account of how communities identify and trust experts without blind deference.

Characters—parts, properties, or activities of organisms—can be individuated in multiple, non-equivalent ways. This paper aims to show how these differences matter, to frame the problem of character individuation methodologically, and to outline a path to resolving it. I describe the main scientific roles for the character concept, and analyze three broad approaches to character individuation: functional, descriptive, and developmental. I explore which approaches are appropriate for which roles, and propose two evolutionary hypotheses to explain why functionally and developmentally individuated characters diverge.

Vitamins are important scientific categories in different contexts. This paper argues that vitamins are investigative kinds in middle-range ontologies: categories subject to open-ended investigation and that track features of the world. Section 2 presents the history of vitamin discovery to illustrate how the introduction of the “vitamin” category and subsequent research led to the identification of many different vitamins. Section 3 explores whether vitamins can be considered natural or conventional kinds. Section 4 argues that vitamins are investigative kinds. Section 5 considers the ontology of vitamins as investigative kinds in a middle-range ontology.

In this paper, I argue that the fact that a discipline is rarely able to secure knowledge is entirely compatible with the idea that acquiring knowledge is aim of that discipline. What’s more, I maintain that progress towards this aim can be made, and measured, even if a discipline has failed to produce any such knowledge. In motivating this controversial view, I appeal to a field which has been almost entirely ignored by the scientific progress literature: astrobiology.