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. (shrink)

Debates about scientific realism are closely connected to almost everything else in the philosophy of science, for they concern the very nature of scientific knowledge. Scientific realism is a positive epistemic attitude toward the content of our best theories and models, recommending belief in both observable and unobservable aspects of the world described by the sciences. This epistemic attitude has important metaphysical and semantic dimensions, and these various commitments are contested by a number of rival epistemologies of science, known collectively (...) as forms of scientific antirealism. This article explains what scientific realism is, outlines its main variants, considers the most common arguments for and against the position, and contrasts it with its most important antirealist counterparts. (shrink)

We often explain by citing an absence or an omission. Apart from the problem of assigning a causal role to such apparently negative factors as absences and omissions, there is a puzzle as to why only some absences and omissions, out of indefinitely many, should figure in explanations. In this paper we solve this ’many absences problem’ by using the contrastive model of explanation. The contrastive model of explanation is developed by adapting Peter Lipton’s account. What initially appears to be (...) only a trivial amendment to Lipton’s Difference Condition enables us both to offer a much more satisfactory solution to the ’many absences problem’ than David Lewis did, and also to explain why explanation in terms of absences and omissions should be so common. (shrink)

To give a causal explanation is to give information about causal history. But a vast amount of causal history lies behind anything that happens, far too much to be included in any intelligible explanation. This is the Problem of Limitation for explanatory information. To cope with this problem, explanations must select for what is relevant to and adequate for answering particular inquiries. In the present paper this idea is used in order to distinguish two kinds of causal explanation, on the (...) grounds of systematic differences in their conditions of relevance and adequacy. It is further argued that these two forms of causal explanation are interdependent and their interaction provides an instrument through which causal knowledge is acquired and enhanced. What we understand causation in the world to be is neither unconditioned regularity, nor counterfactual dependence, but the sum of correct answers to explanatory inquiries of these two interdependent kinds. (shrink)