Cancer biologists ascribe normal functions to parts of cancer. Normal functions are activities that parts of systems are in some minimal sense supposed to perform. Cancer biologists’ finding normality within the abnormality of cancer poses difficulties for two main approaches to normal function. One approach claims that normal functions are activities for which parts are selected. However, some parts of cancers that have normal functions aren’t selected to perform them. The other approach claims that normal functions are part-activities that (typically) contribute to the survival or reproduction of the relevant system. However, cancers are too heterogeneous to establish what (typically) contributes to their progression across a type.

The concept of scaffold is widespread in science and increasingly common in evolutionary biology. While this concept figures in causal explanations, it is not clear what scaffolds are and what role they play in those explanations. Here we present evolutionary scaffolding explanation as a distinct type of explanatory strategy, distinguishing it from other types of evolutionary explanation. By doing so, we clarify the meaning of “scaffold” as a causal concept and its potential contribution to accounts of evolutionary novelty and major transitions.

Adaptationism is often taken to be the thesis that most traits are adaptations. To assess this thesis, it seems we must be able to establish either an exhaustive set of all traits or a representative sample of this set. Either task requires a more systematic and principled way of individuating traits than is currently available. Moreover, different trait individuation criteria can make adaptationism turn out true or false. For instance, individuation based on natural selection may render adaptationism true, but may do so by presupposing adaptationism. In this article, we show how adaptationism depends on trait individuation and that the latter is an open and unsolved problem.

Research in evolutionary ecology on random foraging seems to ignore the possibility that some random foraging is an adaptation not to environmental randomness, but to what Wimsatt called “perceived randomness.” This occurs when environmental features are unpredictable, whether physically random or not. Mere perceived randomness may occur, for example, due to effects of climate change or certain kinds of static landscape variation. I argue that an important mathematical model concerning random foraging doesn’t depend on environmental randomness, despite contrary remarks by researchers. I use computer simulations to illustrate the idea that random foraging is an adaptation to mere perceived randomness.

Measurement of subjective animal welfare creates a special problem in validating the measurement indicators used. Validation is required to ensure indicators are measuring the intended target state, and not some other object. While indicators can usually be validated by looking for correlation between target and indicator under controlled manipulations, this is not possible when the target state is not directly accessible. In this article, I outline a four-step approach using the concept of robustness that can help with validating indicators of subjective animal welfare.

Immunology is a notoriously complex field with distinct concepts and terminology. Yet immunologists regularly and effectively collaborate with other researchers, notably clinicians and experts in population health. How does such “collaboration without convergence” work? This paper offers an answer. Immunology exhibits three features that support collaboration in the absence of major consensus on theories, methods, or concepts. These are a multifaceted target of inquiry, therapeutic aspirations, and a clear interdisciplinary pathway. Building on these features, I sketch a general account of “low-effort interdisciplinarity” and connect this result to recent work on population health.

We examine arguments regarding the use of mechanistic evidence in assessing treatment efficacy and find that advocates and critics of EBM+ have largely been talking past each other due to a difference in focus. We explore aducanumab for the treatment of Alzheimer’s disease as a case that may speak to the role of EBM+ in pharmaceutical regulation. The case suggests the debate may be more fruitful if philosophers confine debates to particular domains of medicine and weigh in prospectively instead of relying on historical cases in which outcomes are known and that are susceptible to hindsight bias.

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.

Recent science funding policy scholars and practitioners have advocated for the use of lotteries, or elements of random chance, as supplementations of traditional peer review for evaluating grant applications. One of the primary motivations for lotteries is their purported openness to innovative research. The purpose of this article is to argue that current proponents of funding science by lottery overestimate the viability of peer review and thus unduly restrict the scope of lotteries in science funding practice. I further show how this analysis suggests a different way of introducing lotteries into science funding policy.

I argue that the classical temperature concept falls apart in special relativity by examining four consilient procedures for establishing classical temperature: Carnot processes, thermometers, kinetic theory, and black-body radiation. I show that their relativistic counterparts demonstrate no such consilience. I suggest two interpretations for this situation: eliminativism akin to simultaneity, or pluralism akin to rotation.

Thermodynamics is an unusual theory. Prominent figures, including J. C. Maxwell and E. T. Jaynes, have suggested that thermodynamics is anthropocentric, and contemporary approaches label thermodynamics a “subjective theory.” Here, we evaluate the arguments for anthropocentrism but conclude that instead of pointing to an anthropocentric view, they point towards a resource-relative understanding of thermodynamics which can be shorn of the “subjective gloss.”

Leibnizian metaphysics underpins the universally held view that spacetime must be inextendible—that it must be “as large as it can be” in a sense. But here we demonstrate a surprising fact within the context of general relativity: the property of inextendibility turns out to be unstable when attention is restricted to certain collections of “physically reasonable” spacetimes.

It is widely accepted by physicists and philosophers of physics alike that there are certain contexts in which general relativity will “break down.” In such cases, one expects to need some as-yet-undiscovered successor theory. This article discusses certain pathologies of general relativity that might be taken to signal that the theory is breaking down and considers how one might expect a successor theory to do better. The upshot is an unconventional interpretation of the “strong cosmic censorship hypothesis.”

Shifts are a well-known feature of the literature on spacetime symmetries. Recently, discussions have focused on so-called dynamic shifts, which by analogy with static and kinematic shifts enact arbitrary linear accelerations of all matter (as well as a change in the gravitational potential). But in mathematical formulations of these shifts, the analogy breaks down: while static and kinematic shift act on the matter field, the dynamic shift acts on spacetime structure instead. I formulate a different, “active,” version of the dynamic shift which does act on matter, and analyse the consequences of this reformulation for Newton–Cartan theory and Maxwell gravitation.

The self-interaction spin-2 approach to general relativity (GR) has been extremely influential in the particle physics community. Leaving no doubt regarding its heuristic value, we argue that a view of the metric field of GR as nothing but a stand-in for a self-coupling field in flat spacetime runs into a dilemma: either the view is physically incomplete in so far as it requires recourse to GR after all, or it leads to an absurd multiplication of alternative viewpoints on GR rendering any understanding of the metric field as nothing but a spin-2 field in flat spacetime unjustified.

Recent accounts of multiscale modeling investigate ontic and epistemic constraints imposed by relations between component models at varying relative scales (macro, meso, micro). These accounts often focus especially on the role of the meso, or intermediate, relative scale in a multiscale model. We aid this effort by highlighting a novel role for mesoscale models: functioning as a focal point, and explanation, for disagreement between researchers who otherwise share theoretical commitments. We present a case study in multiscale modeling of insect behavior to illustrate, arguing that the cognitive map debate in neuroethology research is best understood as a mesoscale disagreement.

The philosophy of historical sciences investigates their distinct objects of study, epistemic challenges, and methodological solutions. Rethinking astronomy in this light offers a contribution. First, the methodology of historical sciences adds to a more adequate description of how astronomers study and utilize token events. Second, astronomy faces a typical difficulty in identifying traces of some past events and has developed a delicate solution. This enriches the idea of trace and suggests a methodology that relies on iterations between data-driven approaches and theory-driven approaches, together with the cross-validation between multiple relevant historical events or datasets.

Philosophers and metrologists have refuted the view that measurement’s epistemic privilege in scientific practice is explained by its theory neutrality. Rather, they now explicitly appeal to the role that theories play in measurement. I formulate a challenge for this view: Scientists sometimes ascribe epistemic privilege to measurements even if they lack a shared theory about their target quantity, which I illustrate through a case study from early geodesy. Drawing on that case, I argue that the epistemic privilege of measurement can precede shared background theory and is better explained by its pretheoretic function in enabling a distinctive kind of inquiry.

Robustness with respect to climate models is often considered by philosophers of climate science to be a crucial issue in determining whether and to what extent the projections of the Earth’s future climate that models yield should be trusted. Wendy Parker and Lisa Lloyd have introduced influential accounts of robustness for climate models with seemingly conflicting conclusions. I argue that Parker and Lloyd are characterizing distinct notions of robustness and providing complementary insights. Confidence, if warranted, need be by virtue of causally consistent climate models rather than by agreement upon projections by a diverse range of models.

Climate scientists frequently employ heavily idealized models. How should these models be interpreted? Some philosophers have advanced a possibilist interpretation: climate models stand in for possible scenarios that could occur but do not provide information about how probable those scenarios are. This article argues that possibilism is (1) undermotivated, (2) incompatible with successful practices in the science, and (3) unable to correct for known biases. The upshot is that the models should be interpreted probabilistically in at least some cases.