In this paper an attempt is made at developing the notion of a real and complete empirical explanation as excluding all forms of potential or incomplete explanations. This explanation is, however, no longer conceived as the proper aim of empirical science, for it can certainly be gleaned from recent epistemological publications that no comprehensive notion of a real and complete scientific explanation is likely to be constructed from within empirical science. Contrary to common understanding the empirical explanation, deductive-nomological as well (...) as statistical explanation, is considered here only as motive of scientific activities, i.e., as common aim of a transcending cooperation of scientific and non-scientific social practice. Following from this the proper aim of empirical science now consists in the development of practically relevant explanatory theories.This redetermination of the aim of scientific activities of empirical science also means criticism of the unification of deductive-nomological and statistical explanations, as it has been proposed by Wolfgang Stegmüller in his pragmatisch-epistemische Wende. For both forms of empirical explanation must be referred to fundamentally different kinds of practical relevance, the former playing a more important role in the advancement of social practice. Stegmüller's development of a comprehensive probabilistic notion of empirical explanation, as tied up to pragmatic knowledge-situations, in a way already transcends a scientifically immanent determination of it, but he seems to have stopped halfway on the road to practically relevant empirical explanations. Several insufficiencies with his probabilistic notion of empirical explanation are shown up in this paper as a consequence of his abiding by pragmatic, and not penetrating to practical, knowledge-situations. The final result of it, however, consists in a clarification and a modification of the concept of deductive-nomological explanation, originally developed by Hempel and Oppenheim. (shrink)

Though the last decade has seen a growing interest in pragmatic approaches to scientific explanation, the question as to the real nature of these attempts has not been answered as yet. Three possibilities are investigated: 1. the pragmatic turn is a kind of linguistic turn where "pragmatic" refers to linguistic pragmatics; 2. the pragmatic turn is a semiotic turn in that the term "pragmatic" should be understood in the sense of semiotic pragmatics; 3. the pragmatic turn is in fact a (...) methodological turn and thus does not consist in relativizing explanations to linguistic situations or interpreters, but it manifests itself in applying a well known but in the theory of science unusual way of model-formation. Assumption is argued for by contrasting two possible senses of the concept "model". As a result, the dividing line must not be drawn between "pragmatic" and "non-pragmatic" accounts of scientific explanation, but between models which constitute necessary and sufficient conditions for correct explanations, and abstract analogical models which use knowledge about a certain fragment of natural language to infer new information about the structure of explanations. The role of pragmatics in the latter type of models is characterized by referring to recent results concerning the question-answer relationship. Finally, the properties of abstract analogical models seem to suggest that the methodological-pragmatic turn is possibly progressive with respect to the special theory of science. (shrink)

This paper describes the development of theories of scientific explanation since Hempel's earliest models in the 1940ies. It focuses on deductive and probabilistic whyexplanations and their main problems: lawlikeness, explanation-prediction asymmetries, causality, deductive and probabilistic relevance, maximal specifity and homogenity, the height of the probability value. For all of these topic the paper explains the most important approaches as well as their criticism, including the author's own accounts. Three main theses of this paper are: (1) Both deductive and probabilistic explanations (...) are important in science, not reducible to each other. (2) One must distinguish between (cause giving) explanations and (reason giving) justifications and predictions. (3) The adequacy of deductive as well as probabilistic explanations is relative to a pragmatically given background knowledge-which does not exclude, however, the possibility of purely semantic models. (shrink)