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.

Kevin Davey claims that the justification of the second law of thermodynamics as it is conveyed by the “standard story” of statistical mechanics, roughly speaking, that low-entropy microstates tend to evolve to high-entropy microstates, is “unhelpful at best and wrong at worst.” In reply, I demonstrate that Davey’s argument for rejecting the standard story commits him to a form of skepticism that is more radical than the position he claims to be stating and that Davey places unreasonable demands on the notion of justification in the physical sciences.

Recently, several funding agencies have introduced the distribution of funds by a lottery system; however, the effects of this system on the productivity of the research community are unclear. Simulation studies in philosophy of science have argued that a combination of peer review and lottery is an optimal method. However, these models overlook several important aspects of research activities, such as baseline funding through block grants. In this article, I present a general theoretical model that incorporates these aspects and argue that the conventional combination of peer review and baseline funding outperforms the combination of peer review and lottery in many situations.

“Actionability” is a key concept in precision oncology. Its precise definition, however, remains contested. This article undertakes a philosophical analysis of “actionability” to aid in conceptual clarification. We map distinct concepts of actionability, arguing that each is best understood as a contextually objective category articulated to mitigate risk of “conceptual slippage.” We defend “interactive pluralism,” acknowledging the need for distinct concepts but also for conceptual interaction in practice. This article thus offers insights for both practitioners and philosophers, clarifying approaches to actionability for scientists and clinicians and serving as a case study to test competing views on scientific pluralism.

Strong emergentism is the position that certain higher-level properties display a kind of metaphysical autonomy from the lower-level properties in which they are grounded. The prospect of collapse is a problem for strong emergentism. According to those who press the collapse problem any purportedly strongly emergent feature inheres in the emergence base and so is not genuinely autonomous from that base. Umut Baysan and Jessica Wilson (2017) argue that power emergentism avoids the collapse problem. In this paper, I challenge the claim that power emergentism avoids the collapse problem and argue for explanatory emergentism in its place.

The different social institutions involved in the development and distribution of science and technology tend to promote, primarily, commercial and private interests, even in situations with high social stakes. Acknowledging how these interests interplay with social and epistemic values is fundamental for understanding the role of values in science today. To show this, I use the global pandemic and the race to develop and distribute vaccines against COVID-19 as an example. I argue that a mere circumstantial alignment of values across the social institutions of science is not enough and that instead we need a more substantive alignment.

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system.

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.

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.

The modern Everett interpretation of quantum mechanics describes an emergent multiverse. The goal of this paper is to provide a perspicuous characterisation of how the multiverse emerges making use of a recent account of (weak) ontological emergence. This will be cashed out with a case study that identifies decoherence as the mechanism for emergence. The greater metaphysical clarity enables the rebuttal of critiques due to Baker (2007) and Dawid and Thébault (2015) that cast the emergent multiverse ontology as incoherent; responses are also offered to challenges to the Everettian approach from Maudlin (2010) and Monton (2013).

Humans are often altruistic in a variety of contexts, even toward strangers they may never meet again. What explains this behavior? Many argue that kin selection cannot explain it but group selection can. Contra this common line of reasoning, I provide two ways that kin selection might help explain the evolution of broad-scope human altruism: in gene-culture coevolution and in a ‘cultural’ version of kin selection.

Formal and social epistemologists have devoted significant attention to the question of how to aggregate the credences of a group of agents who disagree about the probabilities of events. Moss (2011) and Pettigrew (2019) argue that group credences can be a linear mean of the credences of each individual in the group. By contrast, I argue that if the epistemic value of a credence function is determined solely by its accuracy, then we should, where possible, aggregate the underlying statistical models that individuals use to generate their credence functions, using “stacking” techniques from statistics and machine learning first developed by Wolpert (1992).

When Whitehead's views of relativity are mentioned, everyone thinks of the views Whitehead published between 1919 and 1924. Concerning these views, C. D. Broad is “depressed”1 (1: pp. 143–4) that physicists paid so little attention. And Victor Lowe has written:

There is a bare possibility that Whitehead's theory of relativity may yet affect the history of science. (4: p. 69)

Researchers of language origins typically try to explain how compositional communication might evolve to bridge the gap between animal communication and natural language. However, as an explanatory target, compositionality has been shown to be problematic for a gradualist approach to the evolution of language. In this article, I suggest that reflexivity provides an apt and plausible alternative target that does not succumb to the problems that compositionality faces. I further explain how protoreflexivity, which depends on functional reference, gives rise to complex communication systems via modular composition.

Bayesians often appeal to “merging of opinions” to rebut charges of excessive subjectivity. But what happens in the short run is often of greater interest than what happens in the limit. Seidenfeld and coauthors use this observation as motivation for investigating the counterintuitive short run phenomenon of dilation, since, they allege, dilation is “the opposite” of asymptotic merging of opinions. The measure of uncertainty relevant for dilation, however, is not the one relevant for merging of opinions. We explicitly investigate the short run behavior of the metric relevant for merging, and show that dilation is independent of the opposite of merging.

Jarrett Leplin has recently criticized a number of aspects of my views of the aims and goals of science, of the rationale of scientific change, and of the consequent relations between science and the philosophy of science, and in particular of the methodology of the latter (Leplin 1984, 1987, 1988a, 1988b). Here I will respond to those criticisms, and also reply to some related criticisms made by other writers.

Wilfrid Sellars has proposed a materialist account of sensation which relies in part on the postulation of special kinds of individuals. This postulational strategy appears to be analogous to the one that introduces such entities as electrons. After setting out Sellars' account, I focus on his application of the postulational strategy. I argue that this application requires the discovery of new effects for familiar properties; that this kind of discovery is disanalogous to what postulation usually does; and that this kind of discovery cannot really be arrived at by postulation. I conclude that Sellars has not provided a successful, materialist account of sensation.