Nevin Climenhaga

In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s erotetic account are incompatible with IBE; and Salmon’s causal–mechanical model is merely consistent with IBE. In short, many influential models of scientific explanation do not support IBE. I end by outlining three possible conclusions to draw: (1) either philosophers of science or defenders of IBE have seriously misconstrued the concept of explanation, (2) philosophers of science and defenders of IBE do not use the term ‘explanation’ univocally, and (3) the ampliative conception of IBE, which is compatible with any model of scientific explanation, deserves a closer look.

Drawing inspiration from a well-attested historical tradition, I propose an account of cognition according to which knowledge is not only prior to belief; it is also, and crucially, not a kind of belief. Believing, in turn, is not some sort of botched knowing, but a mental state fundamentally different from knowing, with its own distinctive and complementary role in our cognitive life. I conclude that the main battle-line in the history of epistemology is drawn between the affirmation of a natural mental state in which there is a contact between ‘mind’ and ‘reality’ and the rejection of such a natural mental state. For the former position, there is a mental state which is different in kind from belief, and which is constituted by the presence of the object of cognition to the cognitive subject, with no gap between them. For the latter position, all our cognition is belief, and the question becomes how and when belief is permissible.

We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and analyze the differential impact of evidence and credence change at different points within a single network and across different theoretical structures.

The threshold problem is the task of adequately answering the question: “Where does the threshold lie between knowledge and lack thereof?” I start this paper by articulating two conditions for solving it. The first is that the threshold be neither too high nor too low; the second is that the threshold accommodate the significance of knowledge. In addition to explaining these conditions, I also argue that it is plausible that they can be met. Next, I argue that many popular accounts of knowledge cannot meet them. In particular, I lay out a number of problems that standard accounts of knowledge face in trying to meet these conditions. Finally, near the end of this paper, I argue that there is one sort of account that seems to evade these problems. This sort of account, which is called a cluster account of knowledge, says that knowledge is to be accounted for in terms of truth, belief and a cluster of epistemic properties and also that knowledge doesn’t require having all members of the cluster, but merely some subset.

Infallibilism is commonly rejected because it is apparently subject to easy counter-examples. I describe a strategy that infallibilists can use to resist this objection. Because the sentences used in the counter-examples to express evidence and belief are context-sensitive, the infallibilist can insist that such counter-examples trade on a vacillation between different readings of these sentences. I describe what difficulties await those who try to produce counter-examples against which the proposed strategy is ineffective.

Evidential Decision Theory and Causal Decision Theory are the leading contenders as theories of rational action, but both face counterexamples. We present some new counterexamples, including one in which the optimal action is causally dominated. We also present a novel decision theory, Functional Decision Theory, which simultaneously solves both sets of counterexamples. Instead of considering which physical action of theirs would give rise to the best outcomes, FDT agents consider which output of their decision function would give rise to the best outcome. This theory relies on a notion of subjunctive dependence, where multiple implementations of the same mathematical function are considered to have identical results for logical rather than causal reasons. Taking these subjunctive dependencies into account allows FDT agents to outperform CDT and EDT agents in, for example, the presence of accurate predictors.

Paul Draper has recently developed an account of intrinsic probability according to which a theory’s intrinsic probability is determined by its modesty and coherence. He employs this account in an argument that Source Physicalism (SP) and Source Idealism (SI) are equally intrinsically probable. Since SP and SI are not exhaustive, and Theism is one very specific version of SI, it follows that the intrinsic probability of Theism is very low. I argue here that considerations of fundamentality show that more work needs to be done to defend the claim that P (SP) = P(SI).

Recent years have seen the rise of a new family of non-probabilistic accounts of epistemic justification. According to these views—we may call them Normalcy Views—a belief in P is justified only if, given the evidence, there exists no normal world in which S falsely beliefs that P. This paper aims to raise some trouble for this new approach to justification by arguing that Normalcy Views, while initially attractive, give rise to problematic accounts of epistemic defeat. As we will see, on Normalcy Views seemingly insignificant pieces of evidence turn out to have considerable defeating powers. This problem—I will call it the Easy-Defeat Problem—gives rise to a two-pronged challenge. First, it shows that the Normalcy View has counterintuitive implications and, second, it opens the door to an uncomfortable skeptical threat.

Moral grandstanding is a pervasive feature of public discourse. Many of us can likely recognize that we have engaged in grandstanding at one time or another. While there is nothing new about the phenomenon of grandstanding, we think that it has not received the philosophical attention it deserves. In this essay, we provide an account of moral grandstanding as the use of public discourse for moral self-promotion. We then show that our account, with support from some standard theses of social psychology, explains the characteristic ways that grandstanding is manifested in public moral discourse. We conclude by arguing that there are good reasons to think that moral grandstanding is typically morally bad and should be avoided.