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This article explores three ways in which physics may involve counterpossible reasoning. The first way arises when evaluating false theories: to say what the world would be like if the theory were true, we need to evaluate counterfactuals with physically impossible antecedents. The second way relates to the role of counterfactuals in characterizing causal structure: to say what causes what in physics, we need to make reference to physically impossible scenarios. The third way is novel: to model metaphysical dependence in physics, we need to consider counterfactual consequences of metaphysical impossibilities. Physics accordingly bears substantial and surprising counterpossible commitments.

Adrian Currie has introduced a novel account of creativity within the social epistemology of science. The account is intended to capture how conservatism can be detrimental to the health of inquiry within certain scientific communities, given the aims of research there. I argue that recent remarks by Carlo Rovelli put pressure on the applicability of the account. Altogether, it seems we do not yet well understand the relationship between creativity, conservatism, and the health of inquiry in science.

This article presents a new argument for incorporating a distinction between default and deviant values into the formalism of causal models. The argument is based on considerations about how causal reasoners should represent disagreement over causes, and it is defended against an objection that has been raised against earlier arguments for defaults.

The value-ladenness of computer algorithms is typically framed around issues of epistemic risk. In this article, I examine a deeper sense of value-ladenness: algorithmic methods are not only themselves value-laden but also introduce value into how we reason about their domain of application. I call this domain distortion. In particular, using insights from jurisprudence, I show that the use of recidivism risk assessment algorithms (1) presupposes legal formalism and (2) blurs the distinction between liability assessment and sentencing, which distorts how the domain of criminal punishment is conceived and provides a distinctive avenue for values to enter the legal process.

Philosophy of science has witnessed substantial recent debate over the existence of a structural analogue of chaos, which is alleged to spell trouble for certain uses of climate models. The debate over the analogy can and should be separated from its alleged epistemic implications: chaos-like behavior is neither necessary nor sufficient for small dynamical misrepresentations to generate erroneous results. The kind of sensitivity that matters in epistemology is one that induces unsafe beliefs, and the existence of a structural analogue to chaos is better seen as an explanation for known safety failures than as providing evidence for unknown ones.

Normatively inappropriate scientific dissent prevents warranted closure of scientific controversies and confuses the public about the state of policy-relevant science, such as anthropogenic climate change. Against recent criticism by de Melo-Martín and Intemann of the viability of any conception of normatively inappropriate dissent, I identify three conditions for normatively inappropriate dissent: its generation process is politically illegitimate, it imposes an unjust distribution of inductive risks, and it adopts evidential thresholds outside an accepted range. I supplement these conditions with an inference-to-the-best-explanation account of knowledge-based consensus and dissent to allow policy makers to reliably identify unreliable scientific dissent.

I analyze cultural relativism as a methodological strategy to correct for ethnocentric biases in anthropological fieldwork. I discuss the format debiasing norms may adopt (rules or standards) depending on whether a discipline has a causal or interpretative outlook. Franz Boas and his school advocated for an interpretative approach to ethnographic fieldwork, in which cultural relativism was implemented as a standard (only culturally unbiased reports are admissible) to be interpreted by expert third parties. Legitimate as it may be as a debiasing method, it does not allow anthropologists to adjudicate their debates on biases in their ethnographic record.

This article advertises a new account of computational implementation. According to the resemblance account, implementation is a matter of resembling a computational architecture. The resemblance account departs from previous theories by denying that computational architectures are exhausted by their formal, mathematical features. Instead, they are taken to be permeated with causality, spatiotemporality, and other nonmathematical features. I argue that this approach comports well with computer scientific practice and offers a novel response to so-called triviality arguments.

At the beginning of the twentieth century, the French philosopher of science Edmond Goblot wrote three prescient papers on function and teleology. He advanced the remarkable thesis that functions are, as a matter of conceptual analysis, selected effects. He also argued that “selection” must be understood broadly to include both evolutionary natural selection and intelligent design. Here, I do three things. First, I give an overview of Goblot’s thought. Second, I identify his core thesis about function. Third, I argue that, despite its ingenuity, Goblot’s expansive construal of function cannot be right. Still, Goblot deserves long-overdue credit for his work.

An increasing number of arguments for causal pluralism invoke empirical psychological data. Different aspects of causal cognition—specifically, causal perception and causal inference—are thought to involve distinct cognitive processes and representations, and they thereby distinctively support transference and dependency theories of causation, respectively. We argue that this dualistic picture of causal concepts arises from methodological differences, rather than from an actual plurality of concepts. Hence, philosophical causal pluralism is not particularly supported by the empirical data. Serious engagement with cognitive science reveals that the connection between psychological concepts of causation and philosophical notions is substantially more complicated than is traditionally presumed.

Reformulating a scientific theory often leads to a significantly different way of understanding the world. Nevertheless, accounts of both theoretical equivalence and scientific understanding have neglected this important aspect of scientific theorizing. This essay provides a positive account of how reformulation changes our understanding. My account simultaneously addresses a serious challenge facing existing accounts of scientific understanding. These accounts have failed to characterize understanding in a way that goes beyond the epistemology of scientific explanation. By focusing on cases in which we have differences in understanding without differences in explanation, I show that understanding does not reduce to explanation.

In cases in which many causes together bring about an effect, it is common to select some as particularly important. Philosophers since Mill have been pessimistic about analyzing this reasoning because of its variability and the multifarious causal and pragmatic details of how it works. I argue Mill was right to think these details matter but wrong that they preclude philosophical analysis of causal selection. I show that analyzing the pragmatic details of scientific debates about the important causes of the Bhopal Gas Tragedy can illuminate causal reasoning about disasters and shed new light on causality and causal selection.

Mathematics is often taken to play one of two roles in the empirical sciences: either it represents empirical phenomena or it explains these phenomena by imposing constraints on them. This article identifies a third and distinct role that has not been fully appreciated in the literature on applicability of mathematics and may be pervasive in scientific practice. I call this the “bridging” role of mathematics, according to which mathematics acts as a connecting scheme in our explanatory reasoning about why and how two different descriptions of an empirical phenomenon relate to each other. I discuss two bridging roles appearing in biological and physical explanations.

Callender and Cohen have proposed to apply a “Gricean strategy” to the constitution problem of scientific representation. They suggest that scientific representation can be reduced to stipulation by epistemic agents. This account has been criticized for not making a distinction between symbolic and epistemic representation and not taking into account the communal aspects of representation. These criticisms would not apply if Grice’s actual strategy were properly employed. I transpose Grice’s strategy to epistemic representation. The main novelty of the resulting account is a distinction between contextual representational use and general representational status, which I address using the notion of indexicality.

This article examines the role of historical science in clarifying the causal structure of complex natural processes. I reject the pervasive view that historical science does not uncover natural regularities. To show why, I consider an important methodological distinction in geology between uniformitarianism and actualism; methodological actualism, the preferred method of geologists, often relies on historical reconstructions to test the stability of currently observed processes. I provide several case studies that illustrate this, including one that highlights how historical narratives can improve predictive models.

Olav Benjamin Vassend proposes two solutions to the “interpretive problem” of assigning nonzero probabilities to hypotheses that are known to be false. He argues that the verisimilitude interpretation (probability expresses the degree of belief that the hypothesis is closest to the truth) and the counterfactual interpretation (probability is conditional on a false supposition) are equivalent. While Vassend’s intuition about these two solutions is basically correct, the technical details of his treatment need elaboration and correction. Appropriate tools for combining verisimilitude and Bayesian probabilities can be found in my Truthlikeness.

Sometimes retracted or refuted scientific information is used and propagated long after it is understood to be misleading. Likewise, retracted news items may spread and persist, despite being publicly established as false. In this article, we explore the dynamics of retraction using agent-based models of epistemic networks, to see why false beliefs might persist despite retraction. We find that, often, those who received false information simply fail to receive retractions because of social dynamics. Surprisingly, delaying retraction can increase its impact. Further, retractions are most successful when issued by the original source of misinformation, rather than a separate source.

In “Resurrecting Biological Essentialism,” I went against the consensus in the philosophy of biology by arguing that a Linnaean taxon, including a species, has an essence that is, at least partly, an underlying intrinsic, mostly genetic, property: this intrinsic nature explains both the truth of generalizations about the phenotypic properties of the taxon and why being in the taxon is explanatory. The current article is a response to two criticisms: that this intrinsic essentialism is at odds with certain biological variations and that this talk of intrinsic essences is an uncalled for metaphysical addition to biology.

Kirsten Walsh has criticized my interpretation of Newton’s view on the certainty of his new science of color, namely, that it shifted through his long career from one of certainty to probabilism. I defend my view by further considering his statements on certainty in his Optical Lectures, “New Theory about Light and Colors,” Query 31 of the Opticks, and Rule 4 added to the Principia in 1726.

Imagination is important for many things in science: solving problems, interpreting data, designing studies, and much else. Philosophers of imagination typically account for the productive role played by imagination in science by focusing on how imagination is constrained, for example, by self-imposed rules to infer logically or model events accurately. But the constraints offered by these philosophers constrain either too much or not enough, and they can never account for uses of imagination that are needed to break today’s constraints in order to make progress tomorrow. Thus, epistemology of imagination needs to make room for an element of epistemological anarchy.

Several argue that truth cannot be science’s sole epistemic goal, for it would fail to do justice to several scientific practices that advance understanding. I challenge these arguments but only after making a small concession: science’s sole epistemic goal is not truth as such; rather, its goal is finding true answers to relevant questions. Using examples from the natural and social sciences, I then show that scientific understanding’s epistemically valuable features are either true answers to relevant questions or a means thereof.

Mammalian placental pregnancy is a neglected problem case for theories of organismality. This example is closer to home than those typically discussed within philosophy of biology. I apply evolutionary and immunological accounts of organismality to the “counting question”: How many organisms are present during a placental pregnancy? I conclude that an evolutionary approach yields the answer two, because of bottlenecking, germ-soma sequestration, and sexual recombination. By contrast, an immunological approach answers one, because of pervasive interactions across the placenta. This analysis expands and refines recent work on a biologically informed metaphysics of pregnancy, an undertheorized area of philosophy of science.

Most attempts to justify the use of idealized models to explain appeal to the accuracy of the model with respect to difference-making causes. In this article, I argue for an alternative way to justify using idealized models to explain that appeals to universality classes. In support of this view, I show that scientific modelers seeking to explain stable limiting behaviors often explicitly appeal to universality classes in order to justify their use of idealized models to explain.

A number of philosophers draw a close analogy between scientific modeling and fiction, often appealing to Kendall Walton’s make-believe view. I assess the models-fictions analogy from a cognitive angle, suggesting that from this perspective it appears relatively weak. More specifically, I argue that, on the one hand, the appeal to Walton is appropriate inasmuch as his view fits well with how modelers employ the imagination. On the other hand, what makes Walton’s view attractive as an account of the cognitive aspects of modeling makes it less attractive as an account of fiction.

In this article, I first outline the view developed in my recent book on the role of idealization in scientific understanding. I discuss how this view leads to the recognition of a number of kinds of variability among scientific representations, including variability introduced by the many different aims of scientific projects. I then argue that the role of idealization in securing understanding distances understanding from truth but that this understanding nonetheless gives rise to scientific knowledge. This discussion will clarify how my view relates to three other recent books on understanding by Henk de Regt, Catherine Elgin, and Kareem Khalifa.

Typically, the imagination in thought experiments has been taken to consist in mental images; we visualize the state of affairs described. A recent alternative from Fiora Salis and Roman Frigg maintains that it is only the propositional imagination that is necessary for the conduct of a thought experiment. I set out problems with these monistic accounts and develop a pluralist stance. Thought experiments appeal to a variety of our imaginative capacities, and we ought to focus on the function of particular thought experiments when considering what type of imaginative engagement they invite.

Philosophical discussions of information and specificity in biology are now commonplace, but no consensus exists about whether the privileging of genetic causation in investigation and explanation is justified. However, little effort has been expended on understanding practices when scientists experimentally measure information or causal specificity. An example of this type of practice—measuring positional information in gene expression during pattern formation in embryogenesis—shows that biologists are unconcerned with comparing the amount of information in genes with that of other factors. Instead, they focus on whether the measured causal specificity explains the phenomenon under scrutiny.

I argue that diversity and pluralism are valuable not just for science but for philosophy of science. Given the partiality and perspectivism of representation, pluralism preserving integration can increase accuracy. Perspectivism is often supported by appeal to visual representation. I draw further insights from multimodel sensory integration for understanding experiment-based predictions of protein structure. The epistemic lessons learned from the scientific case also apply to philosophy of science itself. Finally, I suggest that a critical, nuanced philosophical view of legitimate sources of pluralism in science has an important role to play in public discourse.

This is an essay review of Deborah G. Mayo's "Statistical Inference as Severe Testing," Cambridge University Press, 2018.

This article examines the multiple realizability thesis within a causal framework. The beginnings of this framework are found in Elliott Sober’s “Multiple Realizability Argument against Reduction,” which argues that the multiple realizability thesis poses no challenge to reductive explanation. While Sober’s causal approach has the potential to reveal new insights, I argue that his setup fails to capture important aspects of the multiple realizability thesis. After correcting for these issues, I argue that this causal framework reveals something quite different. It reveals how multiple realizability relates to a common type of causal complexity in biology that poses problems for reductive explanation.

History is littered with scientifically ill-founded claims about human nature. They frequently appear in normative contexts, projecting ideology or values onto nature (what we call the naturalizing error). In considering a remedy, we adopt a naturalized epistemology approach to how we think about human nature. The “nature” in “human nature” fosters unproductive essentialist thinking, epitomized in the adage “a tiger cannot change its stripes.” Universalist, fixist, and teleological perspectives each erode epistemic reasoning and blur the distinction between normative and descriptive justification. We articulate strategies to guide more responsible claims about human nature in science and science communication.

We report the results of a study that investigated the views of researchers working in seven scientific disciplines and in history and philosophy of science in regard to four hypothesized dimensions of scientific realism. Among other things, we found (i) that natural scientists tended to express more strongly realist views than social scientists, (ii) that history and philosophy of science scholars tended to express more antirealist views than natural scientists, (iii) that van Fraassen’s characterization of scientific realism failed to cluster with more standard characterizations, and (iv) that those who endorsed the pessimistic induction were no more or less likely to endorse antirealism.

Kitcher has proposed an ideal-theory account—well-ordered science (WOS)—of the collective good that science’s research agenda should promote. Against criticism regarding WOS’s action guidance, Kitcher has advised critics not to confuse substantive ideals and the ways to arrive at them, and he has defended WOS as a necessary and useful ideal for science policy. I provide a distinction between two types of ideal theories that helps clarifying WOS’s elusive nature. I use this distinction to argue that the action-guidance problem that WOS faces remains even under the aims/means distinction because the WOS’s failure is more basic than critics have suggested.

The concept of emergence is commonly invoked in modern physics but rarely defined. Building on recent influential work by Jeremy Butterfield, I provide precise definitions of emergence concepts as they pertain to properties represented in models, applying them to some basic examples from space-time and thermostatistical physics. The chief formal innovation I employ, similarity structure, consists in a structured set of similarity relations among those models under analysis—and their properties—and is a generalization of topological structure. Although motivated from physics, this similarity-structure-based account of emergence applies to any science that represents its possibilia with (mathematical) models.

We identify a species of experiment—Kon-Tiki experiments—used to demonstrate the competence of a cause to produce a certain effect, and we examine their role in the historical sciences. We argue that Kon-Tiki experiments are used to test middle-range theory, to test assumptions within historical narratives, and to open new avenues of inquiry. We show how the results of Kon-Tiki experiments are involved in projective (rather than consequentialist) inferences, and we argue (against Kyle Stanford) that reliance on projective inferences does not provide historical scientists with any special protection against the problem of unconceived alternatives.

The canonical formalism of general relativity affords a particularly interesting characterisation of the infamous hole argument. It also provides a natural formalism in which to relate the hole argument to the problem of time in classical and quantum gravity. In this paper, we examine the connection between these two much discussed problems in the foundations of spacetime theory along two interrelated lines. First, from a formal perspective, we consider the extent to which the two problems can and cannot be precisely and distinctly characterised. Second, from a philosophical perspective, we consider the implications of various responses to the problems, with a particular focus upon the viability of a `deflationary' attitude to the relationalist/substantivalist debate regarding the ontology of spacetime. Conceptual and formal inadequacies within the representative language of canonical gravity will be shown to be at the heart of both the canonical hole argument and the problem of time. Interesting and fruitful work at the interface of physics and philosophy relates to the challenge of resolving such inadequacies., Comment: 20 pages (+ references)

The requirement of total evidence is a mainstay of Bayesian epistemology. Peter Fisher Epstein argues that the requirement generates mistaken conclusions about several examples that he devises. Here we examine the example of Epstein’s that we find most interesting and argue that Epstein’s analysis of it is flawed.

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.

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 essay considers a mixed-effects modeling practice and its implications for the philosophical debate surrounding reductive explanation. Mixed-effects modeling is a species of the multilevel modeling practice, where a single model incorporates simultaneously two (or even more) levels of explanatory variables to explain a phenomenon of interest. I argue that this practice makes the position of explanatory reductionism held by many philosophers untenable because it violates two central tenets of explanatory reductionism: single-level preference and lower-level obsession.

According to psychological constructivism, emotions result from projecting folk emotion concepts onto felt affective episodes. While constructivists acknowledge there is a biological dimension to emotion, they deny that emotions are (or involve) affect programs. So they also deny emotions are natural kinds. However, the essential role that constructivism gives to felt experience and folk concepts leads to an account that is extensionally inadequate and functionally inaccurate. Moreover, biologically oriented proposals that reject these commitments are not similarly encumbered. Recognizing this has two implications: biological mechanisms are more central to emotion than constructivism allows, and the conclusion that emotions are not natural kinds is premature.

There is a fairly long-standing distinction between what are called the ideographic as opposed to nomothetic sciences. The nomothetic sciences, such as physics, offer explanations in terms of the laws and regular operations of nature. The ideographic sciences, such as natural history (or, more controversially, evolutionary biology), cast explanations in terms of narratives. This article offers an account of what is involved in offering an explanatory narrative in the historical (ideographic) sciences. I argue that narrative explanations involve two chief components: a possibility space and an explanatory causal mechanism.

James developed an evolutionary objection to epiphenomenalism that is still discussed today. Epiphenomenalists have offered responses that do not grasp its full depth. I thus offer a new reading and assessment of James’s objection. Our life-essential, phenomenal pleasures and pains have three features that suggest that they were shaped by selection, according to James: they are natively patterned, those patterns are systematically linked with antecedent brain states, and the patterns are “universal” among humans. If epiphenomenalism were true, phenomenal patterns could not have been selected (because epiphenomenalism precludes phenomenal consciousness affecting reproductive success). So epiphenomenalism is likely false.

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 tohvaries over time.

This article considers the following question: What is the relationship between supervenience and reduction? I investigate this formally: first, by introducing a recent argument by Christian List to the effect that one can have supervenience without reduction; then, by considering how the notion of Nagelian reduction can be related to the formal apparatus of definability and translation theory; then, by showing how, in the context of propositional theories, topological constraints on supervenience serve to enforce reducibility; and, finally, by showing how constraints derived from the theory of ultraproducts can enforce reducibility in the context of first-order theories.

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.

Information is widely perceived as essential to the study of communication and representation; still, theorists working on these topics often take themselves not to be centrally concerned with "Shannon information", as it is often put, but with some other, sometimes called "semantic" or "nonnatural",kind of information. This perception is wrong. Shannon's theory of information is the only one we need. I intend to make good on this last assertion by canvassing a fully (Shannon) informational answer to the metasemantic question of what makes something a representation, for a certain important family of cases. This answer and the accompanying theory, which represents a significant departure from the broadly Dretskean philosophical mainstream, will show how a number of threads in the literature on naturalistic metasemantics, aimed at describing the purportedly non-informational ingredients in representation, actually belong in the same coherent, purely information-theoretic picture.

The concept of disease remains hotly contested. In light of problems with existing accounts, some theorists argue that the disease concept ought to be eliminated. We answer this skeptical challenge by reframing the discussion in terms of the role that the disease concept plays in the complex network of health care institutions in which it is deployed. We argue that while prevailing accounts do not suffer from the particular defects that critics have identified, they do suffer from other deficits, and this leads us to propose a new account that satisfies the desiderata for a concept of disease in human medicine.

Recent philosophy of measurement has emphasized the existence of both diachronic and synchronic “loops,” or feedback processes, in the epistemic achievements of measurement. A widespread response has been to conclude that measurement outcomes do not convey interest-independent facts about the world and that only a coherentist epistemology of measurement is viable. In contrast, I argue that a form of measurement realism is consistent with these results. The insight is that antecedent structure in measuring spaces constrains our empirical procedures such that successful measurement conveys a limited but veridical knowledge of “fixed points,” or modally stable, interest-independent features of the world.