Uncertainty and Quality in Science for Policy

By Silvio Funtowicz, Jerome Ravetz. 1990

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Citations in the corpus

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward (2020, methodology): “Tools of post-normal-science inspiration for knowledge and modelling quality assessment could be adapted to the analysis of algorithms, such as the NUSAP (Numeral Unit Spread Assessment Pedigree) notation system for the management and communication of uncertainty (Funtowicz and Ravetz, 1990; Van Der”
Future research challenges for incorporation of uncertainty in environmental and ecological decision-making (2008, background): “Funtowicz and Ravetz (1990) describe uncertainty as a ituation of three kinds of inadequate information: inexactess, unreliability, and border with ignorance.”
GLOBAL MULTIREGIONAL INPUT–OUTPUT FRAMEWORKS: AN INTRODUCTION AND OUTLOOK (2013, background): “That is, a problem that can be framed as a scientific question, but that cannot be solved entirely scientifically (Weinberg, 1972; Funtowicz and Ravetz, 1990; Wynne, 1992).”
An overview of sustainability assessment methodologies (2009, background): “A notational system called NUSAP (an acronym for five categories: Numeral, Unit, Spread, Assessment, Pedigree) can be used to characterise the quality of quantitative information based in large part on the experience of research work in the matured natural sciences (Funtowicz and Ravetz, 1990).”
Defining Uncertainty: A Conceptual Basis for Uncertainty Management in Model-Based Decision Support (2003, unknown): “Others are more general, not targeted specifically on model-based decision support (such as [3,11]) or apply to a specific context, such as water management (e.”
Uncertainty in the environmental modelling process - A framework and guidance (2007, background): “Some are rather generic, such as Funtowicz and Ravetz (1990), while others apply more specifically to model based water management, such as Beck (1987).”
Scientific and technological uncertainty, the precautionary principle, scenarios and risk management (2001, background): “A probabilistic risk assessment may be possible but both data uncertainties and model uncertainties will be large (Funtowicz and Ravetz, 1990) (hence the reference to scienti c judgement in the CSTEE opinion above).”
Tools for Composite Indicators Building (2005, background): “A notational system called NUSAP (an acronym for five categories: Numeral, Unit, Spread, Assessment, Pedigree) has been devised to characterise the quality of quantitative information based in large part on the experience of research work in the matured natural sciences (Funtowicz and Ravetz, 1990).”
Tracking the evolution of waste recycling research using overlay maps of science. (2011, background): “sciplinary Intermediation Low High Monodisciplinary Interdisciplinary 10 a result, the emphasis is not simply on the incidental value of multiple indicators or their collective ranges of variability (Funtowicz and Ravetz, 1990). The aim is also to focus deliberate, self conscious, critical attention”
The precautionary principle in environmental science. (2001, unknown): “This may result from a confusion of uncertainty of information with quality of information; but the two concepts are distinct (37).”
Agent-based Models of Geographical Systems (2012, background): “Edmonds, C. Hernandez, & K. Troitzsch (Eds.), Social simulation: Technologies, advances and new discoveries (pp. 81–97). Hershey: GI Global. Pujol, J. M., Flache, A., Delgado, J., & Sangüesa, R. (2005). How can social networks ever become complex? Modelling the emergence of complex networks from loc”