I argue that understanding why p involves a kind of intellectual know how and differsfrom both knowledge that p and knowledge why p (as they are standardly understood).I argue that understanding, in this sense, is valuable.

Among philosophers of science there seems to be a general consensus that understanding represents a species of knowledge, but virtually every major epistemologist who has thought seriously about understanding has come to deny this claim. Against this prevailing tide in epistemology, I argue that understanding is, in fact, a species of knowledge: just like knowledge, for example, understanding is not transparent and can be Gettiered. I then consider how the psychological act of "grasping" that seems to be characteristic of understanding (...) differs from the sort of psychological act that often characterizes knowledge. Zagzebski's account Kvanvig's account Two problems Comanche cases Unreliable sources of information The upper-right quadrant So is understanding a species of knowledge? A false choice. (shrink)

In this paper we explore the constraints that our preferred account of scientific representation places on the ontology of scientific models. Pace the Direct Representation view associated with Arnon Levy and Adam Toon we argue that scientific models should be thought of as imagined systems, and clarify the relationship between imagination and representation.

Let E be a set of n propositions E1, ..., En. We seek a probabilistic measure C(E) of the ‘degree of coherence’ of E. Intuitively, we want C to be a quantitative, probabilistic generalization of the (deductive) logical coherence of E. So, in particular, we require C to satisfy the following..

If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a sufficient but not slavish sensitivity (...) to the facts. (shrink)

It is tempting to think that, if a person's beliefs are coherent, they are also likely to be true. This truth conduciveness claim is the cornerstone of the popular coherence theory of knowledge and justification. Erik Olsson's new book is the most extensive and detailed study of coherence and probable truth to date. Setting new standards of precision and clarity, Olsson argues that the value of coherence has been widely overestimated. Provocative and readable, Against Coherence will make stimulating reading for (...) epistemologists and anyone with a serious interest in truth. (shrink)

Coherence is a measure of how much our beliefs hang together. Understanding is achieved when we see that something is not just a brute, isolated fact. This suggests that it might be possible to use the extant probabilistic measures of coherence to formulate a measure of understanding. We attempt to do so, but it turns out that a coherence theory runs into trouble with the asymmetry of understanding. We identify four difficulties and show how they have been solved by a (...) unification approach to explanation. We also identify four advantages of the coherence approach, and assess the possibilities of reconciling the strengths of the two approaches.La coherencia es una medida sobre cuanta interdependencia hay entre nuestras creencias. La comprension se obtiene cuando vemos que algo no es un hecho bruto, aislado. Esto sugiere la posibilidad de usar las medidas probabilisticas de coherencia al uso para elaborar una medida de la comprension. Explorare esta posibilidad, a pesar de que una teoria de la coherencia tropieza con problemas aqui dado el caracter asimetrico de la comprension. Identifico cuatro dificultades al respecto y muestro como han sido resueltas mediante un enfoque de la explicacion basado en la nocion de unificacion. Tambien identifico cuatro ventajas en la aproximacion desde la coherencia y examino que perspectivas hay de reconciliar los puntos fuertes de ambos planteamientos. (shrink)

Several authors suggest that understanding and epistemic coherence are tightly connected. Using an account of understanding that makes no appeal to coherence, I explain away the intuitions that motivate this position. I then show that the leading coherentist epistemologies only place plausible constraints on understanding insofar as they replicate my own account’s requirements. I conclude that understanding is only superficially coherent.

Paulina Sliwa (2015) argues that knowing why p is necessary and sufficient for understanding why p. She tries to rebut recent attacks against the necessity and sufficiency claims, and explains the gradability of understanding why in terms of knowledge. I argue that her attempts do not succeed, but I indicate more promising ways to defend reductionism about understanding why throughout the discussion.

How can a model that stops short of representing the whole truth about the causal production of a phenomenon help us to understand the phenomenon? I answer this question from the perspective of what I call the simple view of understanding, on which to understand a phenomenon is to grasp a correct explanation of the phenomenon. Idealizations, I have argued in previous work, flag factors that are casually relevant but explanatorily irrelevant to the phenomena to be explained. Though useful to (...) the would-be understander, such flagging is only a first step. Are there any further and more advanced ways that idealized models aid understanding? Yes, I propose: the manipulation of idealized models can provide considerable insight into the reasons that some causal factors are difference-makers and others are not, which helps the understander to grasp the nature of explanatory connections and so to better grasp the explanation itself. (shrink)