Summary Research is regarded as transformations of complexes composed of knowledge, problems and (hardware and software) instruments. Sequences of such transformations are embedded in human settings in which they are given directions. Problems and the work of solving them are divided into empirical and theoretical ones. In an advanced science like physics empirical and theoretical work are interrelated by means of flows of problem-generating information. Empirical and theoretical researchers work also on problems of their own making. Residuals of knowledge which (...) cannot be systematized at the same rate as it is produced as well as clashes between new and old knowledge are potential starting points of new lines of research. (shrink)

A rule for the acceptance of scientific hypotheses called 'the principle of cost-benefit dominance' is shown to be more effective and efficient than the well-known principle of the maximization of expected utility. Harvey 's defense of his theory of the circulation of blood in animals is examined as a historical paradigm case of a successful defense of a scientific hypothesis and as an implicit application of the cost-benefit dominance rule advocated here. Finally, various concepts of 'dominance' are considered by means (...) of which the effectiveness of our rule may be increased. (shrink)

A rule for the acceptance of scientific hypotheses called ‘the principle of cost-benefit dominance’ is shown to be more effective and efficient than the well-known principle of the maximization of expected (epistemic) utility. Harvey's defense of his theory of the circulation of blood in animals is examined as a historical paradigm case of a successful defense of a scientific hypothesis and as an implicit application of the cost-benefit dominance rule advocated here. Finally, various concepts of ‘dominance’ are considered by means (...) of which the effectiveness of our rule may be increased. (shrink)

In pure science, the standard approach to non-epistemic values is to exclude them as far as possible from scientific deliberations. When science is applied to practical decisions, non-epistemic values cannot be excluded. Instead, they have to be combined with scientific information in a way that leads to practically optimal decisions. A normative model is proposed for the processing of information in both pure and applied science. A general-purpose corpus of scientific knowledge, with high entry requirements, has a central role in (...) this model. Due to its high entry requirements, the information that it contains is sufficiently reliable for the vast majority of practical purposes. However, for some purposes, the corpus needs to be supplemented with additional information, such as scientific indications of danger that do not satisfy the entry requirements for the corpus. The role of non-epistemic values in the evaluation of scientific information should, as far as possible, be limited to determining the level of evidence required for various types of practical decisions. (shrink)

The few extant arguments concerning the autonomy of science in the rational acceptance of hypotheses are examined. It is concluded that science is not morally autonomous, and that the attendant notion of rationality in science decisionmaking is inadequate. A more comprehensive notion of scientific rationality, which encompasses the old one, is proposed as a replacement. The general idea is that scientists qua scientist ought, in their acceptance decisions, to take into account the ethical consequences of acceptance as well as the (...) consequences with regard to the attainment of "purely scientific" or "epistemic" objectives. The result constitutes an argument for a (presumably cooperative) game theoretic treatment of inductive logic. (shrink)

Ordinary Language Philosophy has largely fallen out of favour, and with it the belief in the primary importance of analyses of ordinary language for philosophical purposes. Still, in their various endeavours, philosophers not only from analytic but also from other backgrounds refer to the use and meaning of terms of interest in ordinary parlance. In doing so, they most commonly appeal to their own linguistic intuitions. Often, the appeal to individual intuitions is supplemented by reference to dictionaries. In recent times, (...) Internet search engine queries for expressions of interest have become quite popular. Apparently, philosophers attempt to surpass the limits of their own linguistic intuitions by appealing to experts or to factual uses of language. I argue that this attempt is commendable but that its execution is wanting. Instead of appealing to dictionaries or Internet queries, philosophers should employ computer-based linguistic corpora in order to confirm or falsify hypotheses about the factual use of language. This approach also has some advantages over methods employed by experimental philosophers. If the importance of ordinary language is stressed, the use of linguistic corpora is hardly avoidable. (shrink)