Uncertainty and Quality in Science for Policy

Abstract

Uncertainty and quality are crucial aspects of knowledge for science related to policy. Hitherto the skills of managing them have been neglected, partly because of the metaphysical prejudices that mathematical language is inherently precise and scientific assertions necessarily correct. In this age of global environmental problems, there is an urgent need for a method of expressing judgements of uncertainty and quality that is convenient, robust and nuanced. The notational system NUSAP (Numeral, Unit, Spread, Assessment, Pedigree) has been created to fill this need. In this book NUSAP is explained and applied 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.