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)

Science is praxis relevant to the extent that it guides goal-directed action by telling us how to act in order to achieve the goals. Investigations aiming at high praxis relevance are performed in various disciplines under names such as clinical trials, evaluation research, intervention research and social experiments. In this contribution, the notion of (direct) praxis relevance is delineated, and it is distinguished from related properties of science such as those of being applied and being practically useful in a wider (...) sense. Recommendations for the achievement of praxis relevance are offered in the form of five principles: the prerogative of direct experiments, minimized theory-induced uncertainty, multiple approximations, causal chain decomposition and successive improvements. (shrink)