The Pessimistic Induction (PI) states: most past scientific theories were radically mistaken; therefore, current theories are probably similarly mistaken. But mistaken in what way? On the usual understanding, such past theories are false. However, on widely held views about reference and presupposition, many theoretical claims of previous scientific theories are neither true nor false. And if substantial portions of past theories are truth-valueless, then the PI leads to semantic antirealism. But most current philosophers of science reject semantic antirealism. So PI proponents face a difficult choice: accept either semantic antirealism or an unorthodox position on reference and presupposition.

Philosophers’ traditional emphasis on theories, theoretical modeling, and explanation misguides research in philosophy of science. Articulating and applying core theories is part of scientific practice, but it is not the essence of scientific practice. Insofar as science has an essence, it is to systematically investigate and learn about what is not yet understood. This lecture analyzes genetics to articulate a broad-practice-centered approach to philosophy of science. It concludes by arguing that this approach can lead to richer, deeper, and more useful philosophies of science, philosophies that can better inform science policy and the public’s understanding of science.

Definitions of animal welfare often invoke consciousness or sentience. Marian Stamp Dawkins has argued that to define animal welfare this way is a mistake. In Dawkins’s alternative view, an animal with good welfare is one that is healthy and “has what it wants.” The dispute highlights a source of strain on the concept of animal welfare: consciousness-involving definitions are better able to capture the normative significance of welfare, whereas consciousness-free definitions facilitate the validation of welfare indicators. I reflect on how the field should respond to this strain, ultimately recommending against splitting the concept and in favor of consciousness-involving definitions.

The neural reuse framework developed primarily by Michael Anderson proposes that brain regions are involved in multiple and diverse cognitive tasks and that brain regions flexibly and dynamically interact in different combinations to carry out cognitive functioning. We argue that the evidence cited by Anderson and others falls short of supporting the fundamental principles of neural reuse. We map out this problem and provide solutions by drawing on recent advances in network neuroscience, and we argue that methods employed in network neuroscience provide the means to fully engage in a research program operating under the principles of neural reuse.

This essay unpacks a seeming paradox: a concept used to formulate, promote, and legitimate oppressive ideologies—a concept used to formulate mistaken, because they were typological, biological theories about human diversity—is, it seems, the same concept that now promises to deliver wonderful, socially sensitized, innovative results in social and genetic epidemiology. But how could that be? How could scientists expect a concept as problematic as ordinary race to deliver useful scientific results? I propose that there is a process for retranslating Ballungen race concepts in appropriate ways to make them fit and work within social scientific and bioscientific contexts.

Leading philosophical accounts presume that Thomas H. Morgan's transmission theory can be understood independently of experimental practices. Experimentation is taken to be relevant to confirming, rather than interpreting, the transmission theory. But the construction of Morgan's theory went hand in hand with the reconstruction of the chief experimental object, the model organism Drosophila melanogaster. This raises an important question: when a theory is constructed to account for phenomena in carefully controlled laboratory settings, what knowledge, if any, indicates the theory's relevance to phenomena outside highly controlled settings? The answer, I argue, is found within the procedural knowledge embedded within laboratory practice.

In recent years, several authors have called to ground descriptive and normative decision theory on neuropsychological measures of utility. In this article, I combine insights from the best available neuropsychological findings, leading philosophical conceptions of welfare, and contemporary decision theory to rebut these prominent calls. I argue for two claims of general interest to philosophers, choice modelers and policy makers. First, severe conceptual, epistemic, and evidential problems plague ongoing attempts to develop accurate and reliable neuropsychological measures of utility. Second, even if these problems are solved, neuropsychological measures of utility lack the potential to directly inform welfare analyses and policy evaluations.

Is the quantum-logic interpretation dead? Its near total absence from current discussions about the interpretation of quantum theory suggests so. While mathematical work on quantum logic continues largely unabated, interest in the quantum-logic interpretation seems to be almost nil, at least in Anglo-American philosophy of physics.

This paper has the immodest purpose of changing that fact. I shall argue that while the quantum-logic interpretation faces challenges, it remains a live option. The usual objections either miss the mark, or admit a reasonable answer, or fail to decide the issue conclusively.

Paul Griffiths et al. have proposed a quantitative measure of causal specificity and used it to assess various attempts to single out genetic causes as being causally more specific than other cellular mechanisms, for example, alternative splicing. Focusing in particular on developmental processes, they have identified a number of important challenges for this project. In this discussion note, I would like to show how these challenges can be met.

This article introduces and motivates the notion of a “properly extensive” quantity by means of a puzzle about the reliability of certain canonical length measurements. An account of these measurements’ success, I argue, requires a modally robust connection between quantitative structure and mereology that is not mediated by the dynamics and is stronger than the constraints imposed by “mere additivity.” I outline what it means to say that length is not just extensive but properly so and then briefly sketch an application of proper extensiveness to the project of providing a reductive ground for metric quantitative structure.

Scientists can choose different claims as interpretations of the results of their research. Scientific rhetoric is understood as the attempt to make those claims most beneficial for the scientists’ interests. A rational choice, game-theoretic model is developed to analyze how this choice can be made and to assess it from a normative point of view. The main conclusion is that ‘social’ interests (pursuit of recognition) may conflict with ‘cognitive’ ones when no constraints are put on the choices of the authors of scientific papers, as in an ‘ideal free speech situation’. Scientific institutions may help to solve this conflict. Lastly, some empirical predictions are offered that can inspire future social research of the refereeing process.

Eric Scerri and other authors have acknowledged that the reality of chemical orbitals is not compatible with quantum mechanics. Recently, however, Scerri and Sharon Crasnow have argued that if chemists cannot consider orbitals as real entities, then chemistry is in danger of being reduced to physics. I argue that the question of the existence of orbitals is best viewed as an issue of explanation, not metaphysics: In many chemically important cases orbitals do not make sufficiently accurate predictions, and must be replaced. Chemists and physicists can acknowledge this fact while maintaining the utility of orbitals and the autonomy of chemistry.

In a previous article, we have demonstrated by a general phase space argument that a Maxwellian Demon is compatible with statistical mechanics. In this article, we show how this idea can be put to work in the prevalent model of the Demon, namely, a particle-in-a-box, used, for example, by Szilard and Bennett. In the literature, this model is used in order to show that a Demon is incompatible with statistical mechanics, either classical or quantum. However, we show that a detailed phase space analysis of this model illustrates that a Maxwellian Demon is compatible with statistical mechanics.

Helen Longino's “contextual empiricism” is one of the most sophisticated recent attempts to defend a social theory of science. On this view, objectivity and epistemic acceptability require that research be produced within communities that approximate a Millian marketplace of ideas. I argue, however, that Longino's embedding of her epistemology within the framework of Mill's political liberalism implies a conception of individual epistemic agents that is incompatible with her view that scientific knowledge is necessarily social, and I begin to articulate an alternative conception that is better suited to a truly social theory of science.

This article argues that scale dependence of physical and biological processes offers resistance to reductionism and has implications that support a specific kind of downward causation. I demonstrate how insights from multiscale modeling can provide a concrete mathematical interpretation of downward causation as boundary conditions for models used to represent processes at lower scales. The autonomy and role of macroscale parameters and higher-level constraints are illustrated through examples of multiscale modeling in physics, developmental biology, and systems biology. Drawing on these examples, I defend the explanatory importance of constraining relations for understanding the behavior of biological systems.

The “Cosmological Constant Problem” (CCP) is widely considered a crisis in contemporary theoretical physics. Unfortunately, the search for its resolution is hampered by open disagreement about what is, strictly, the problem. This disagreement stems from the observation that the CCP is not a problem within any of our current theories, and nearly all of the details of those future theories for which the CCP could be made a problem are up for grabs. Given this state of affairs, I discuss how one ought to make sense of the role of the CCP in physics and generalize some lessons from it.

This paper discusses different interpretations of probability in relation to determinism. It is argued that both objective and subjective views on probability can be compatible with deterministic as well as indeterministic situations. The possibility of a conceptual independence between probability and determinism is argued to hold on a general level. The subsequent philosophical analysis of recent advances in classical statistical mechanics (ergodic theory) is of independent interest, but also adds weight to the claim that it is possible to justify an objective interpretation of probabilities in a theory having as a basis the paradigmatically deterministic theory of classical mechanics.

The measurement of force is based on a formal law of additivity, which characterizes the effects of two or more configurations on the equilibrium of a material point. The representing vectors (resultant forces) are additive over configurations. The existence of a tight interrelation between the force vector and the geometric space, in which motion is described, depends on observations of partial (directional) equilibria; an axiomatization of this interrelation yields a proof of part two of Newton's second law of motion.

The present results (which were derived from a curious and deep isomorphism between force measurement and trichromatic color measurement) yield a kind of subunit, which needs to be incorporated into more complete axiomatizations of mechanics that would fulfill the Mach–Kirchhoff program.