Abstract:

The use of probabilistic models, as in Bayesian analysis, assumes some sort of model stability: populations of similar units need to be constructed. But such stability is often not fulfilled. An extended approach is thus required, and a framework for such an approach is conceptualistic pragmatism which links the probabilistic analysis with knowledge theory and the quality movement with its focus on continuous improvement. In this paper we restrict attention to the applications of probabilistic models in a risk assessment context. The purpose of the paper is to investigate how conceptualistic pragmatism may work as a suitable framework for such an extended approach in a risk assessment context. The key to make the framework operational is to perform broad analyses of uncertainties.