作者: Ian Scoones , Andy C. Stirling
DOI:
关键词: Normative 、 Risk assessment 、 Surprise 、 Value (ethics) 、 Simple (philosophy) 、 Management science 、 Ignorance 、 Accountability 、 Engineering 、 Ambiguity 、 Risk analysis (engineering)
摘要: Governance of infectious disease risks requires understanding often indeterminate interactions between diverse, complex, open, and dynamic human natural systems. In the face these challenges, worldwide policy making affords disproportionate status to " science-based" risk-assessment methods. These reduce multiple, complex dimensions simple quantitative parameters "outcomes" "probabilities," then re-aggregate across diverse metrics, contexts, perspectives yield a single ostensibly definitive picture risk. contrast, more precautionary or participatory approaches are routinely portrayed as less rigorous, complete, robust. Yet, although conventional reductive-aggregative techniques provide powerful responses narrow state risk, they not applicable tractable conditions uncertainty, ambiguity, ignorance. Strong sensitivities divergent framings can render results highly variable. Reductive aggregation marginalize important compound exposure surprise. The value broad-based may be appreciated. offer ways rigorous complete in mapping different framings. They also robust than appraisal methods, "opening up" greater accountability for intrinsically normative judgements decision on threats like pandemic avian influenza.