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A Framework for Risk Governance Revisited

  • Ragnar Löfstedt
  • Marjolein van Asselt
Part of the International Risk Governance Council Bookseries book series (IRGC, volume 1)

Risk managers like models; they use them to compartmentalise the world they operate in. Good models offer ways to better assess and cope with risks. Over the past decades, a multitude of risk management models has been proposed, some more useful than others. Among the most well known are the National Research Council's 1983 report Federal Risk Assessment-Managing the Process, which calls for separation of risk assessment from risk management (NRC 1983), the National Research Council's 1996 report Understanding Risk: Informing Decisions in a Democratic Society, which argues for a risk characterisation process to be implemented throughout the entire risk analysis process (NRC 1996) and the UK Royal Commission for Environmental Pollution 1998 report Setting Environmental Standards, which argues that the articulation of people's values should more or less be incorporated in risk management processes (RCEP 1998). Models for risk management are neither easy to develop, nor are they by definition useful for policy makers. Good risk management models need to be easily understood in order to be usable by risk management practitioners, while at the same time such models should reflect the scholarly state of the art. They are simplified versions of a complex body of knowledge. In other words, sound frameworks for risk management are both as sophisticated and as simple as possible. Developing a risk management model thus requires synthesis of available insights as well as simplification and translation into easy to understand schemes and recommendations. This is the challenge the International Risk Governance Council (IRGC) took on in developing its risk governance framework.

Keywords

Risk Management Risk Communication Precautionary Principle Health Council Risk Governance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2008

Authors and Affiliations

  • Ragnar Löfstedt
    • 1
  • Marjolein van Asselt
    • 2
  1. 1.King's Centre for Risk ManagementKing's College LondonUK
  2. 2.Faculty of Arts and Social SciencesMaastricht UniversityThe Netherlands

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