AuthorGRIMES, THOMAS RICHARD.
AdvisorPollock, John L.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThe problem of scientific explanation as it pertains to the explanation of singular facts or events turns on the problem of characterizing the nature of explanatory relevance. In motivating an account of this relation, I examine the views of explanation advanced by Carl Hempel, Wesley Salmon, and Bas van Fraassen. I defend Hempel's covering-law model against the traditional objections which have been raised against it, and then argue that this model ultimately fails on grounds that it is typically impossible to fill in the explanans in sufficient detail so as to effect a sound derivation of the explanandum. In regard to Salmon's causal theory, I seek to demonstrate that his account of causation can not be successfully applied to the problem of explanation. I then present some general considerations which indicate that no purely causal analysis of explanation will work. For van Fraassen's pragmatic proposal, I try to show that the formal constraints he places on explanation are both too weak and too strong. In addition, given that van Fraassen allows explanatory relevance to be most anything a person wants it to be, I question whether he has clarified the nature of this relation in any interesting way. To overcome the problems encountered by these three major views, I suggest that explanatory relevance is a nomological relation which is to be analyzed in terms of the notion of nomic responsibility. I then characterize this notion on the basis of subjunctive probability relations which are tied to counterlegal situations. In addressing the problem of statistical explanation, I argue that the notion of explanation admits of degrees to the effect that some events are objectively more explainable than others. Thus, both high and low probability events can be explained, but only partially.