Uncertainty and Quality in Science for Policy [Paperback]

This book explains the notational system NUSAP (Numeral, Unit, Spread, Assessment, Pedigree) and applies it to several examples from the environmental sciences. The authors are now making further extensions of NUSAP, including an algorithm for the propagation of quality-grades through models used in risk and safety studies. They are also developing the concept of `Post-normal Science', in which quality assurance of information requires the participation of `extended peer-communities' lying outside the traditional expertise.

60 -I 137.0~29 ERROR BARS tONE (1 \ \ \ 4\0 \ \ E \ a. a. \ Z30 \ 137.0388 \ 0 137.0377 \ ~ \ ~20 \ \ 0 to 0 '50 Fig.1. Successive recommended values of the fine-structure constand IX-I (B. N. Taylor et 01., 1969,7) reminder that the value is not fully accepted by colleagues, since they will expect it to jump about for a while longer. Our next example is taken from a recent study in the social sciences. It shows how a set of related estimates of uncertainty can be expressed clearly and effectively by NUSAP. Suppose that we wish to forecast what the future price of a basic commodity might be, especially when at the moment its price is artificially maintained by a cartel of producers. There is no experimental evidence on such a future contingency, and yet we are not completely in the dark. There is a long history of expertise in the field; and there is a well-tried standard model by which experts' guesses can be translated into mathematical form.Prologue.Introduction: Some Illustrative Examples.1. Science for Policy: Uncertainty and Quality.2. Uncertainty and its Management.3. The Mathematical Language.4. Craft Skills with Numbers.5. Measurement.6. Maps.7. Mathematical Notations: Functions and Design.8. The NUSAP Notational Scheme: Introduction.9. The NUSAP Categories: Numeral, Unit and Spread.10. The NUSAP Categories: Assessment and Pedigree.11. The Pedigree for Statistical Information.12. Mapping the Uncertainties of Radiologl³Ÿ