Social Unrest

image of Social Unrest

This report develops a framework of social unrest within a complex understanding of systemic risk.  The goal is to  try to identify triggers (events that lead to social unrest) and drivers (causal roots) for the emergence of social unrest and, based on this functional analysis, to design policy options on how to avoid, mitigate or handle unrest. The framework should enable a better understanding of the circumstances that may trigger social unrest, how intensely that unrest is likely to materialize and what interventions promise  to de-escalate the conflict or even prevent social unrest in the first place.   Since social unrest is more a process of escalation than a finite state of the world, the term has been conceptualized in a step-by-step escalation scheme.   Each step makes social unrest more severe. It is a gradual framework that identifies the different stages that make social unrest more and more probable. In order to identify relevant drivers and cluster of drivers, three case studies are investigated:  pandemics, cyber-related risk and financial crises. The main question is how did or could these events cause social unrests.  In a second step, an analytic model is used to capture the combined effects learned from the case study analysis. In a third step,the IRGC risk governance model for explaining the risk of social unrest or predicting the consequences of social unrest is applied. Finally , guidelines for normative governance with respect to social unrest are developed.



Normative governance

Risk governance denotes both the institutional structure and the policy process that guide and restrain collective activities of a group, society or international community to regulate, reduce or control risk problems. Risk governance has shifted from traditional state-centric approaches with hierarchically organized governmental agencies as the dominant locus of power to multi-level systems, in which the political authority for handling risk problems is distributed to distinct public bodies with overlapping jurisdictions that do not match the traditional hierarchical order (cf. Skelcher 2005; Hooghe and Marks, 2003). This implicates an increasingly multilayered and diversified socio-political landscape in which a multitude of actors, their perceptions and evaluations draw on a diversity of knowledge and evidence claims, value commitments and political interests in order to influence processes of risk analysis, decision-making and risk management (Jasanoff, 2004). Institutional diversity can offer considerable advantages when complex, uncertain and ambiguous risk problems such as social unrest need to be addressed because, first, risk problems with different scopes can be managed at different levels, second, an inherent degree of overlap and redundancy makes non-hierarchical adaptive and integrative risk governance systems more resilient and therefore less vulnerable, and third, the larger number of actors facilitates experimentation and learning (Renn, 2008). Disadvantages refer to the possible co-modification of risk; the fragmentation of the risk governance process; costly collective risk decision-making; and the potential loss of democratic accountability (Charnley, 2000).


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