Foundations of Science 12 (3):257-268 (2007)

Authors
Sven Ove Hansson
Royal Institute of Technology, Stockholm
Abstract
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
Keywords Corpus  Values in science  Epistemic values  Non-epistemic values  Scientific values  Applied science  Pure science
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DOI 10.1007/s10699-007-9107-6
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References found in this work BETA

The Fixation of Belief.C. S. Peirce - 1877 - Popular Science Monthly 12 (1):1--15.
Valuation and Acceptance of Scientific Hypotheses.Richard C. Jeffrey - 1956 - Philosophy of Science 23 (3):237-246.
Inductive Inconsistencies.Carl Gustav Hempel - 1960 - Synthese 12 (4):439-69.
Philosophical Perspectives on Risk.Sven Ove Hansson - 2004 - Techné: Research in Philosophy and Technology 8 (1):10-35.

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Citations of this work BETA

Cutting the Gordian Knot of Demarcation.Sven Ove Hansson - 2009 - International Studies in the Philosophy of Science 23 (3):237-243.
The Epistemic Norms of Intra-Scientific Testimony.Mikkel Gerken - 2015 - Philosophy of the Social Sciences 45 (6):568-595.
Understanding Scientific Study Via Process Modeling.Robert W. P. Luk - 2010 - Foundations of Science 15 (1):49-78.

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