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Uncertainty and Quality in Science for Policy

  • Book
  • © 1990

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Part of the book series: Theory and Decision Library A: (TDLA, volume 15)

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Table of contents (16 chapters)

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About this book

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.

Authors and Affiliations

  • Commission of the European Communities, Joint Research Center, Ispra, Italy

    Silvio O. Funtowicz

  • The Research Methods, Consultancy Ltd., London, UK

    Jerome R. Ravetz

About the authors

S.O. Funtowicz is a Visiting Scientist at the European Community Joint Research Centre at Ispra (Varese), Italy. He has taught mathematics, logic and research methodology in Buenos Aires, Argentina.

J.R. Ravetz is the Chairman of the Council for Science and Society in London. He was formerly Reader in the History and Philosophy of Science at the University of Leeds. His previous writings include Scientific Knowledge and its Social Problems (Oxford, 1971) and The Merger of Knowledge with Power (Cassel, 1990).

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