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 ...
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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.
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Add this copy of Uncertainty and Quality in Science for Policy to cart. $168.69, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2011 by Springer.
Add this copy of Uncertainty and Quality in Science for Policy to cart. $168.69, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 1990 by Springer.
This book basically challenges the viewpoint that science can provide clear answers. In a well-controlled laboratory set-up, a chemist may indeed do pretty precise measurements. But in questions of societal concern, the situation is different. The facts are uncertain, the phenomena are poorly understood, and the stakes are high. Climate change is a case in point. Any scientist that claims that the global temperature will have increased by 1.8 degrees by the year 2100, is not doing science. Worse, it often happens that a scientist that is doing his work for an oil company will find a lower value than one whi is speaking on behalf of an environmentalist NGO. Not because they have been hired to write an incorrect report, but because they have access to a different selection of facts and opinions.
This book discusses many situations in which science may not be expected to be as accurate, objective, and free of stakes, as the public or the politicians may believe.
In addition, this book offers a framework for articulating results together with the uncertainty of these results. The book argues that traditional statistics is a too limited vehicle for this, because a statistical analysis requires numbers, and this is precisely what is lacking. Instead, it offers the NUSAP framework, where the P stands for the pedigree, a standardized qualitative way of assessing and communicating the confidence of a numerical result.
While the book can be considered as making a strong and compelling statement, it is a pity that it contains quite some flaws: typos, bad formatting, etc. It reflects the typical style of modern publishers to take manuscripts as given, with minimal editing. A real pity for such an important book!
