Identification of Triggers in a Risk Cycle That Elevate Civil Protests to Terror Events

Identification of triggers in a risk cycle that elevate civil protests to terror events:

The management of adaptive risks for transportation

Matthew Competiello, Elizabeth City State University, Applied Research in Environmental Sciences (ARIES); Bernadette Franklin, SUNY Fredonia (ARIES); Kyle Horne, Central College of Speech and Drama, University of London (ARIES); Noelle Francois, The College of William and Mary (ARIES), Email: ,

Anne Garland, Email: , Lloyd Mitchell, Elizabeth City State University, Haskell Foundation, Email: .

USC, National Center of Risk and Economic Analysis of Terrorism Events

Research Area: Risk, Economics, and Decision Sciences

Problem Statement: When civil disturbance and terror events occur, there is a process or cycle of risks that can be examined to identify changes as a consequence of intentional threats. Adaptations occur in behavior, attitude and knowledge that result in a continuum of reactions to official efforts at risk reduction. This project examines adaptive risk in local, tribal, and regional communities where civil protest has escalated to unrest, civil disturbances, or terror events. The intention is to develop methods that identify triggers of unacceptable risk thereby providing mitigation targets. Six case studies related to transportation and goods distribution were reviewed: three in Tribally Inclusive Geographic Areas (TIGA) and three in non-TIGA. All case studies used were specific for civil disturbance that escalated, some of which resulted in intention terror events.

Methodology: Case study variables were examined for relevance to the changes in adaptive risk. These Variables of Relevance (VOR) include political, social, economic, ideological, geographical, and chronological. Within these variables, Factors of Relevance (FOR) are identified to determine impact changes to threats and civil impacts. From observations of the FOR, Indicators of Relevance (IOR), regarding the behavior, attitude, and knowledge of those causing threats, are scored according to a graduated scale of adaptive risk (SAR). A Cumulative Adaptive Risk Score (CARS) and Averaged Adaptive Risk Score (AARS) are derived from the scale of indicators. Final scores reflect factors and variables of risk cycles.

Data Collection: Data from case studies was compared with field research and real-time data. Risk cycles were reviewed several times weekly; data was integrated to create scores.

Results to Date: Application of the methods includes a case study in New York related to civil impacts of a railroad line in a TIGA. This case includes a history of civil protests, unrest, disturbances and an attempted terror event within its risk cycle.

Future Research/References: Unitive research, which combines qualitative and quantitative components in a software product, will be developed and distributed for use in both TIGA and non-TIGA. Additionally, a program to share potential critical real-time escalations identified in the risk cycle with local leaders via e-notices will be created.

Friend, B., Garland, A., Baldwin, K. Mitchell, L. “Achieving state, local, and tribal integration using a risk matrix and real time reporting in an effort to reduce the economic impact of disaster and terror events,” DHS Summit, Washington, DC, March 1-20 2010.