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.

The cultural red king effect occurs when discriminatory bargaining practices emerge because of a disparity in learning speed between members of a minority and a majority. This effect has been shown to occur in some Nash Demand Game models and has been proposed as a tool for shedding light on the origins of sexist and racist discrimination in academic collaborations. This article argues that none of the three main strategies used in the literature to support the epistemic value of these models—structural similarity, empirical confirmation, and how-possibly explanations—provide strong support for this modeling practice in its present form.

Forber and Smead (2014) analyze how increasing the fitness benefits associated with prosocial behavior can increase the fitness of spiteful individuals relative to their prosocial counterparts, so that selection favors spite over prosociality. This poses a problem for the evolution of prosocial behavior: As the benefits of prosocial behavior increase, it becomes more likely that spite, not prosocial behavior, will evolve in any given population. In this article, I develop two game-theoretic models that, taken together, illustrate how synergistic costs and benefits may provide partial solutions to Forber and Smead’s paradox.

Mixed-methods research (MMR)—the combination of qualitative and quantitative data within the same design to strengthen causal inference—is gaining prominence in the social sciences but its benefits are contested. There remains confusion over which methods to mix and what is the point of mixing them. We argue that variety of evidence is what matters, not of data or methods, and that distinct epistemic principles underlie its added value for causal inference. The centrality of evidential variety also implies that strong causal pluralism is untenable as a foundation for MMR.

Like Austin’s “performatives,” some models are used not merely to represent but also to change their targets in various ways. This article argues that Austin’s analysis can inform model evaluation: If models are evaluated with respect to their adequacy-for-purpose, and if performativity can in some cases be regarded as a model purpose (a proposition that is defended, using mechanism design as an example), it follows that these models can be evaluated with respect to their “felicity,” that is whether their use has achieved this purpose. Finally, I respond to epistemic and ethical concerns that might block this conclusion.

How should one discount utility across time? The conventional wisdom in social science is that one should use an exponential discount function. Such a function is a representation of the axioms that provide a well-defined utility function plus a condition known as stationarity. Yet stationarity doesn’t really have much intuitive normative pull on its own. Here I try to cast it in a normative glow by deriving stationarity from two explicitly normative premises, both suggested by the philosophical thesis of temporal neutralism. Putting the argument in this form helps us better understand exponential discounting and challenges to it.

Recent advocates of “field philosophy” make the case that philosophy “needs to get outside more often”; alongside disciplinary modes of practice we should cultivate philosophical work that is consequential in real-world, practical terms. This takes a number of different forms, many of them captured by a framework for analyzing engaged philosophy of science proposed by Plaisance and Elliott. I draw on three examples of field-engaged philosophy of science that address the legacies of settler-colonialism archaeology to illustrate the promise of field philosophy.