Kareem Khalifa

Our best social scientific theories try to tell us something about the social world. But is talk of a “social world” a metaphor that we ought not take too seriously? In particular, do the denizens of the social world—cultural values like the Protestant work ethic, firms like ExxonMobil, norms like standards of dress and behavior, institutions like the legal system, teams like FC Barcelona, conventions like marriages—exist? The question is not merely academic. Social scientists use these different social entities to explain social phenomena such as the rise of capitalism, the decline in oil prices, or the effect of unions on the sports labor market. But how could these explanations possibly work if social entities don’t exist?

The ontology of race is often seen as answering two central questions. First, do races exist? Second, if races do exist, then what are they? Consequently, determining the best methods for answering these questions falls within the metaontology of race. Within the ontology of race, it is common to select a privileged representation of race in order to draw ontological lessons. While ontological lessons are direct answers to the ontological questions raised above, privileged representations are the basis for inferring those lessons. Using the Office of Management and Budget’s racial classification as an illustration, we argue that certain social-scientific methods are better than mainstream methods at ruling out just-so stories about race, and therefore outperform more mainstream philosophical methods in determining which representations of race should be privileged. In defending this position, we also argue that the widespread philosophical practice of sharply distinguishing social-scientific from ordinary-language conceptions of race is unmotivated.

We present a novel kind of “socio-functional” foundationalism rooted in the division of scientific labor. Our foundationalism is social in that it involves a socio-epistemic phenomenon we dub epistemic outsourcing, whereby claims from one group of scientists provide epistemological foundations for another group of scientists. We argue that: (1) epistemic outsourcing results in a legitimate form of epistemic foundationalism, (2) this sort of foundationalism can be used to shed light on the epistemology of measurement; and (3) epistemic outsourcing is a distinctively collective epistemic phenomenon.

This essay presents a fully inferentialist-expressivist account of scientific representation. In general, inferentialist approaches to scientific representation argue that the capacity of a model to represent a target system depends on inferences from models to target systems. Inferentialism is attractive because it makes the epistemic function of models central to their representational capacity. Prior inferentialist approaches to scientific representation, however, have depended on some representational element, such as denotation or representational force. Brandom’s Making It Explicit provides a model of how to fully discharge such representational vocabulary, but it cannot be applied directly to scientific representations. Pursuing a strategy parallel to Brandom’s, this essay begins with an account of how surrogative inference is justified. Scientific representation and the denotation of model elements are then explained in terms of surrogative inference by treating scientific representation and denotation as expressive, analogous to Brandom’s account of truth. The result is a thoroughgoing inferentialism: M is a scientific representation of T if and only if M has scientifically justified surrogative consequences that are answers to questions about T.

In earlier work, I criticized de Regt’s contextual theory of understanding, and advertised the advantages of my own, knowledge-based account. Using the early history of the standard model in particle physics as an illustration, I instead consider the benefits of unifying these two accounts of understanding. I argue that de Regt’s account substantially improves my own account of explanatory consideration, and that my account of explanatory comparison substantially improves upon his account of explanatory evaluation. De Regt and my apparent disagreement about the so-called factivity of understanding is defused through a voluntaristic approach to the scientific realism debates.

Among epistemologists, it is common to assume that insofar as coherence bears on the justification of belief, the only relevant coherence relations are those _within_ an individual subject’s web of beliefs. After clarifying this view and exploring some plausible motivations for it, we argue that this individualistic account of the epistemic relevance of coherence fails to account for central facets of scientific practice. In its place we propose a social account of coherence. According to the view we propose, a scientist _S_’s belief that _p_ is _prima facie_ unjustified if this belief negatively coheres with justified scientific claims in her scientific community. This account of coherence yields an epistemology for scientific belief which, we argue, has all of the benefits and none of the liabilities of its more individualistic predecessor.

We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. We conclude from this that topological explanations are autonomous from their mechanistic counterparts.

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

Criticism is a staple of the scientific enterprise and of the social epistemology of science. Philosophical discussions of criticism have traditionally focused on its roles in relation to objectivity, confirmation, and theory choice. However, attention to criticism and to criticizability should also inform our thinking about scientific pursuits: the allocation of resources with the aim of developing scientific tools and ideas. In this paper, we offer an account of scientific pursuitworthiness which takes criticizability as its starting point. We call this the apokritic model of pursuit. Its core ideas are that pursuits are practices governed by norms for asking and answering questions, and that criticism arises from the breach of these norms. We illustrate and advertise our approach using examples from institutional grant review, neuroscience, and sociology. We show that the apokritic model can unify several indices of criticizability, that it can account for the importance of criticizing pursuits in scientific practice, and that it can offer ameliorative advice to erstwhile pursuers.

Proponents of ontic conceptions of explanation require all explanations to be backed by causal, constitutive, or similar relations. Among their justifications is that only ontic conceptions can do justice to the ‘directionality’ of explanation, i.e., the requirement that if X explains Y , then not-Y does not explain not-X . Using topological explanations as an illustration, we argue that non-ontic conceptions of explanation have ample resources for securing the directionality of explanations. The different ways in which neuroscientists rely on multiplexes involving both functional and anatomical connectivity in their topological explanations vividly illustrate why ontic considerations are frequently (if not always) irrelevant to explanatory directionality. Therefore, directionality poses no problem to non-ontic conceptions of explanation.

In this paper, we argue that a person is obligated to explain why p just in case she has a role-responsibility to answer the question “Why p?”. This entails that the normative force of explanatory obligations is fundamentally social. We contrast our view with other accounts of explanatory obligations or the so-called “need for explanation,” in which the aforementioned normative force is epistemic, determined by an inquirer's interests, or a combination thereof. We argue that our account outperforms these alternatives.

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.

Many epistemologists endorse true-belief monism, the thesis that only true beliefs are of fundamental epistemic value. However, this view faces formidable counterexamples. In response to these challenges, we alter the letter, but not the spirit, of true-belief monism. We dub the resulting view “inquisitive truth monism”, which holds that only true answers to relevant questions are of fundamental epistemic value. Which questions are relevant is a function of an inquirer’s perspective, which is characterized by his/her interests, social role, and background assumptions. Using examples of several different scientific practices, we argue that inquisitive truth monism outperforms true-belief monism.

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 non-epistemic 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 non-epistemic values need not be restricted to belief or acceptance in order to be relevant to hypothesis choice: the relevance of non-epistemic values to a particular cognitive attitude with respect to h vary over time.

In epistemology and philosophy of science, there has been substantial debate about truth’s relation to understanding. “Non-factivists” hold that radical departures from the truth are not always barriers to understanding; “quasi-factivists” demur. The most discussed example concerns scientists’ use of idealizations in certain derivations of the ideal gas law from statistical mechanics. Yet, these discussions have suffered from confusions about the relevant science, as well as conceptual confusions. Addressing this example, we shall argue that the ideal gas law is best interpreted as favoring non-factivism about understanding, but only after delving a bit deeper into the statistical mechanics that has informed these arguments and stating more precisely what non-factivism entails. Along the way, we indicate where earlier discussions have gone astray, and highlight how a naturalistic approach furnishes more nuanced normative theses about the interaction of rationality, understanding, and epistemic value.

Responding to recent concerns about the reliability of the published literature in psychology and other disciplines, we formed the X-Phi Replicability Project to estimate the reproducibility of experimental philosophy. Drawing on a representative sample of 40 x-phi studies published between 2003 and 2015, we enlisted 20 research teams across 8 countries to conduct a high-quality replication of each study in order to compare the results to the original published findings. We found that x-phi studies – as represented in our sample – successfully replicated about 70% of the time. We discuss possible reasons for this relatively high replication rate in the field of experimental philosophy and offer suggestions for best research practices going forward.

Recent literature on non-causal explanation raises the question as to whether explanatory monism, the thesis that all explanations submit to the same analysis, is true. The leading monist proposal holds that all explanations support change-relating counterfactuals. We provide several objections to this monist position. 1Introduction2Change-Relating Monism's Three Problems3Dependency and Monism: Unhappy Together4Another Challenge: Counterfactual Incidentalism4.1High-grade necessity4.2Unity in diversity5Conclusion

In this essay, we extend earlier inferentialist-expressivist treatments of traditional logical, semantic, modal, and representational vocabulary (Brandom 1994, 2008, 2015; Peregrin 2014) to explanatory vocabulary. From this perspective, Inference to the Best Explanation (IBE) appears to be an obvious starting point. In its simplest formulation, IBE has the form: A best explains why B, B; so A. It thereby captures one of the central inferential features of explanation. An inferentialist-expressivist treatment of “best explains” would treat it as a logical operator. Analogous to the inferentialist-expressivist treatment of other logical operators, this essay aims to provide introduction and elimination rules for “best explains.” Indeed, by exhibiting a form of detachment, IBE superficially looks like an elimination rule. The sequent calculus LEA+, described in Section 5 below, makes good on this intuition. By showing how “A best explains why B” is related to the underlying, scientific inference “A, so B,” we can purchase the inference ticket of IBE for no more than the cost of science’s material inferences

Many epistemologists take Inference to the Best Explanation (IBE) to be “fundamental.” For instance, Lycan (1988, 128) writes that “all justified reasoning is fundamentally explanatory reasoning.” Conee and Feldman (2008, 97) concur: “fundamental epistemic principles are principles of best explanation.” Call them fundamentalists. They assert that nothing deeper could justify IBE, as is typically assumed of rules of deductive inference, such as modus ponens. However, logicians account for modus ponens with the valuation rule for the material conditional. By contrast, fundamentalists account for IBE with an ill-defined set of relations that happen to furnish their favorite set of inductive inferences. To our eye, this seems a little too convenient—there is too much room for ad hoc, just-so stories about the “striking” correspondence between our explanatory and inductive practices. We will argue that the (explanatory) pluralism adopted by the leading theorists of the best explanation—philosophers of science—undermines fundamentalism. Section 1 clarifies fundamentalism’s key tenets. Section 2 presents pluralism’s challenge to fundamentalism. Section 3 considers a potential fundamentalist reply to this challenge. Sections 4 through 6 canvass the leading candidates for developing this fundamentalist reply, showing each to be unsatisfactory.