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.

The problem of theory choice and model selection is hard but still important when useful truths are underdetermined, perhaps not by all kinds of data but by the kinds of data we can have access to ethically or practicably—even if we have an infinity of such data. This article addresses a crucial instance of that problem: the problem of inferring causal structures from nonexperimental, nontemporal data without assuming the so-called causal Faithfulness condition or the like. A new account of epistemic evaluation is developed to solve that problem and justify a standard practice of causal inference in data science.

This article poses a challenge to Schurz’s proposed metainductive justification of induction. It is argued that Schurz’s argument requires a notion of optimality that can deal with an expanding pool of prediction strategies.

This article aims to complement causal model approaches to causal explanation by James Woodward, Joseph Halpern and Judea Pearl, and Michael Strevens. It centers on a strengthened Ramsey Test of conditionals: $\alpha \gg \gamma$ if and only if, after suspending judgment about α and γ, an agent can infer γ from the supposition of α (in the context of further beliefs in the background). Holger Andreas and Mario Günther used this conditional as the starting point of an analysis of ‘because’ in natural language. I refine this analysis so as to yield a fully fledged account of (deterministic) causal explanation.

I draw on speech act theory to understand the speech acts appropriate to the multiple aims of scientific practice and the role of nonepistemic values in evaluating speech acts made relative to those aims. First, I consider work that distinguishes explanatory speech acts from descriptive speech acts within scientific practice. I then show how speech act theory provides a framework to make sense of explaining’s and describing’s distinct felicity conditions. Finally, I argue that if explaining aims to convey understanding to particular audiences rather than describe literally across contexts, then evaluating explanatory speech acts directed to nonscientists involves nonepistemic criteria.

We offer a new account of the role of values in theory choice that captures a temporal dimension to the values themselves. We argue that nonepistemic values sometimes serve as “inquiry tickets,” justifying scientists’ pursuit of certain questions in the short run, while the answers to those questions mitigate transient underdetermination in the long run. Our account of inquiry tickets shows that the role of nonepistemic values need not be restricted to belief or acceptance in order to be relevant to hypothesis choice: the relevance of nonepistemic values to a particular cognitive attitude with respect to h varies over time.

I argue that collaborators do not need to reach broad agreement over the justification of a consensus claim. This is because maintaining a diversity of justifiers within a scientific collaboration has important epistemic value. I develop a view of collective justification that depends on the diversity of epistemic perspectives present in a group. I argue that a group can be collectively justified in asserting that P as long as the disagreement among collaborators over the reasons for P is itself justified. In conclusion, I make a case for multimethod collaborative research and work through an example in the social sciences.

Women are cited less frequently than men in a variety of scientific fields. Drawing theoretical resources from Fricker and Hookway, I argue that these gendered citation practices constitute a form of participatory epistemic injustice insofar as they prevent female scientists from fully engaging in the epistemic practices of science. Furthermore, Longino’s notion of “uptake” gives us a way of understanding gendered citation practices as an epistemic harm accrued not simply by individuals but by scientific communities as a whole. Finally, I discuss the cumulative harms of this kind of participatory epistemic injustice for individuals and for marginalized groups.

Whereas much of the literature in the social epistemology of scientific knowledge has focused either on scientific communities or research groups, we examine the epistemic significance of scientific/intellectual movements (SIMs). We argue that certain types of SIMs can play an important epistemic role in science: they can remedy epistemic injustices in scientific practices. SIMs can counteract epistemic injustices effectively because many forms of epistemic injustice require structural and not merely individual remedies. To illustrate our argument, we discuss the case of indigenous studies.

This article supports calls for an increased integration of patients into taxonomic decision making in psychiatry by arguing that their exclusion constitutes a special kind of epistemic injustice: preemptive testimonial injustice, which precludes the opportunity for testimony due to a wrongly presumed irrelevance or lack of expertise. Here, this presumption is misguided for two reasons: (1) the role of values in psychiatric classification and (2) the potential function of first-person knowledge as a corrective means against implicitly value-laden, inaccurate, or incomplete diagnostic criteria sets. This kind of epistemic injustice leads to preventable epistemic losses in psychiatric classification, diagnosis, and treatment.

This article characterizes various species concepts in terms of set-theoretic models that license biological inferences and illustrates the logical connections among different species concepts. Species in this construal are abstract models, rather than biological or even tangible entities, and relate to individual organisms via representation, rather than the membership or mereological whole/part relationship. The proposal sheds new light on vexed issues of species and situates them within broader philosophical contexts of model selection, scientific representation, and scientific realism.

Evolutionary conceptions of species place special weight on each species having dynamic independence as a unit of evolution. However, the idea that species have their own historical fates, tendencies, or roles has resisted systematic analysis. Growing evidence from population genomics shows that many paradigm species regularly engage in hybridization. How can species be defined in terms of independent evolutionary identities if their genomes are dynamically coupled through lateral exchange? I introduce the concept of a “composite lineage” to distinguish species and subspecies on the basis of the proportion of a group’s heritable traits that are uncoupled from reproductive exchange.

This article defends lineage pluralism; the view that biological lineages are not a single, unified type of entity. I analyze aspects of evolutionary theory, phylogenetics, and developmental biology to show that these areas appeal to distinct notions of lineage. I formulate three arguments for lineage pluralism. These arguments undercut the main motivations for lineage monism; the view that biological lineages are a single, unified type of entity. Although this view is rarely made explicit, it is often assumed in philosophy and biology. Hence, this article sheds light on this monistic assumption and shows why lineage pluralism should be adopted instead.

This article focuses on recent discussions about holobionts and evolutionary individuality to evaluate the merits of integrative pluralism. I argue that integrative pluralism is the wrong approach to take when it comes to holobiont research because integrative pluralism is not liberal enough to accommodate both single-species and multispecies individuals. I conclude by suggesting two points. First, a pluralistic view helps us better understand holobiont research. Second, the case of holobionts helps us develop a better account of scientific pluralism.

Critics of multiple realizability have recently argued that we should concentrate solely on actual here-and-now realizations that are found in nature. The possibility of alternative, but unactualized, realizations is regarded as uninteresting because it is taken to be a question of pure logic or an unverifiable scenario of science fiction. However, in the biological context only a contingent set of realizations is actualized. Drawing on recent work on the theory of neutral biological spaces, the article shows that we can have ways of assessing the modal dimension of multiple realizability that do not have to rely on mere conceivability.

Occam’s razor refers to the idea that among competing explanations the simplest should be preferred. This principle has been understood and defended in different ways. Some systems biologists argue that traditional molecular biology is misguided because it relies on an unjustified application of Occam’s razor. I analyze which version of the principle is relevant in this context and ask whether the allegation stands up to scrutiny by looking at actual research. I defend the traditional approach by arguing that its use of Occam’s razor is innocuous and by showing that systems biology heavily relies on considerations of simplicity as well.

Theories of function are conventionally divided up into historical and ahistorical ones. Proponents of ahistorical theories often cite the ahistoricity of their accounts as a major virtue. Here, I argue that none of the mainstream “ahistorical” accounts are actually ahistorical. All of them refer, implicitly or explicitly, to history. In Boorse’s goal-contribution account, history is latent in the idea of statistical typicality. In the propensity theory, history is implicit in the idea of a species’ natural habitat. In the causal role theory, history is required for making sense of dysfunction. I elaborate some consequences for the functions debate.

The article examines the relationship between a trait’s effect on survival and reproduction and the notion of functional efficiency underlying the biostatistical theory of health (BST). BST faces the problem of how to measure a trait’s joint effect on survival and reproduction in its account of function. If one measures the joint effect by means of the biological notion of fitness, examples such as the hereditary breast and ovarian cancer syndrome do not count as a disorder. If one does not invoke biological fitness, it is unclear how to measure the joint effect while keeping to BST’s naturalist credentials.