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Strategies of community‐based disaster risk reduction have been advocated for more than 2 decades. However, we still lack in‐depth quantitative assessments of the effectiveness of such strategies. Our research is based on a national experiment in this domain: the "Comprehensive Disaster Reduction Demonstration Community" project, a governmental program running in China since 2007. Information on more than 11,000 demonstration communities was collected. Combined with the local disaster information and socioeconomic conditions, the spatiotemporal characteristics of these communities over 12 years and their differences in performance by region and income group were analyzed. We performed an attribution analysis for disaster risk reduction effectiveness. This is the first time a series of quantitative evaluation methods have been applied to verify the effectiveness of a large‐scale community‐based disaster risk reduction project, both from the perspective of demonstrative effects and loss reduction benefits. Here, we find that the project is obviously effective from these two perspectives, and the disaster loss reduction effectiveness illustrates clear regional differences, where the regional economic level and hazard severity act as important drivers. Significant differences of urban‐rural and income call for matching fortification measures, and the dynamic management of demonstration community size is required, since the loss reduction benefit converges when the penetration rate of the demonstration community reaches approximately 4% in a province. These and further results provide diverse implications for community‐based disaster risk reduction policies and practices. [ABSTRACT FROM AUTHOR]

It is essential for public and corporate decision makers to know what dimensions of a strategic issue are important to the public. Contends that European citizens see catastrophic climate impacts as quite possible and do not view scientific uncertainty as a reason for not taking action. (Contains over 20 references.) (WRM)

The global financial crisis of 2008 has shown that the present financial system involves global systemic risks. The dimension of these risks is hard to grasp with the conceptual tools that have been developed to tackle conventional risks like fire or car accidents. While modern societies know quite well how to deal with conventional risks, we have not yet been equally successful at dealing with global systemic risks. For managing this kind of risks, one needs to understand critical features of specific global systems where many human agents interact in ever changing complex networks. Here we apply two specific dimensions of complexity theory for dealing with global systemic risk in an integrated fashion: normal accidents and extended evolution. Both of them have successfully been applied to the analysis of systemic risks. As a paradigmatic example of global systemic risks, we focus on the global financial crisis that began in 2008, and suggest that the future evolution of the financial system could either see a further increase in complexity, or a reversal to a less complex system. We explore and contrast the implications of normal accident theory and extended evolution perspectives and suggest a four‐point research strategy informed by complexity theory for better understanding global systemic risks in financial systems. [ABSTRACT FROM AUTHOR]