Jerry Ravetz

Combining Quantitative and Qualitative Measures of Uncertainty in Model Based Environmental Assessment. The NUSAP System.

This article discusses recent experiences with the Numeral Unit Spread Assessment Pedigree (NUSAP) system for multidimensional uncertainty assessment, based on four case studies that vary in complexity. We show that the NUSAP method is applicable not only to relatively simple calculation schemes but also to complex models in a meaningful way and that NUSAP is useful to assess not only parameter uncertainty but also (model) assumptions. A diagnostic diagram can be used to synthesize results of quantitative analysis of parameter sensitivity and qualitative review (pedigree analysis) of parameter strength. It provides an analytic tool to prioritize uncertainties according to quantitative and qualitative insights in the limitations of available knowledge. We show that extension of the pedigree scheme to include societal dimensions of uncertainty, such as problem framing and value-laden assumptions, further promotes reflexivity and collective learning. When used in a deliberative setting, NUSAP pedigree assessment has the potential to foster a deeper social debate and a negotiated management of complex environmental problems.

Science for the Twenty‐First Century: From Social Contract to the Scientific Core

The article addresses the need, posed by the challenges of sustainable development and the changing context at the beginning of the 21st century, for changes in the method and practice of science. The major challenges for a “sustainability science” arise from increasing complexification at the ontological, epistemological and political levels, calling for an integrated science going far beyond an interdisciplinary style of research. The requirement is for the development, adoption, and dissemination of a truly complex-systems scientific research model. Complex socio-ecological systems share a number of fundamental properties that require changes in scientific methods, criteria of truth and quality, and conceptual frameworks. These properties include non-linearity, plurality of perspectives, emergence of properties, self-organization, multiplicity of scales, and irreducible uncertainty. Some implications of the analysis are pointed out, in the form of practical recommendations. The authors argue for the involvement of both natural and social scientists in the investigation of the necessary steps to develop a sustainability science.

Post-Normal Science. Science and Governance under Conditions of Complexity

Policy-related research issues are particularly challenging for science. They include masses of detail concerning many particular topics, which require separate analysis and management. At the same time, there are broad strategic considerations which should guide regulatory work, such as those connected with precaution, safety or sustainability. Nothing can be managed in a convenient isolation; problems are mutually implicated extending across many scale levels of space and time; and uncertainties and value-loadings of all sorts and all degrees of severity affect data and theories alike.

Ciência pós-normal e comunidades ampliadas de pares face aos desafios ambientais

The new issues of risk and the environment have common features that distinguish them from traditional scientific problems: uncertain facts, values in dispute, high stakes, and a pressing need for decision-making. The problem-solving strategy appropriate to this context can be called post-normal science. The essential function of quality assurance and critical assessment can no longer be performed only by a restricted corps of insiders. The dialogue on quality, along with that on policy, must be extended to all those who have a stake in the issue, that is, to the extended peer community.