Abstract
This chapter examines a model of dynamic causality of violent extremism and a concomitant a structured professional judgment (SPJ) individual risk assessment tool for the spectrum of violent extremism. The analytical approach, referred to as the VERA-2, an acronym for Violent Extremist Risk Assessment- Version 2, is a systematic, consistent, and reliable evidence-based tool. The approach assists an analyst to arrive at a reliable adjudicated level of overall risk for an individual through the application of a rigorous, scientific and transparent methodology. A risk level rating is obtained through an evaluation of relevant risk promoting and risk mitigating indicators supported by an evidence-base. Assessments are undertaken at specified points in time employing the comprehensive set of the risk related indicators. Repeated use of this tool over successive time points provides the analyst with a trajectory of risk as well as risk levels judgments at a specified time on each of the included risk indicators as well as for overall risk. With dynamic systems, there is a need to monitor behavioral changes in an individual on discrete risk elements. The approach facilitates this task and identifies the most salient elements of the individualized risk pattern. This facilitates the development of relevant and focused intervention programs for countering violent extremism (CVE) initiatives, supports investigations and provides defensible prioritization of persons of interest. The tool is effective for determining efficacy of intervention programs via the ability to measure change in individuals on risk related indicators from a pre-determined baseline. The tool includes a comprehensive list of 31 indicators. Limitations and benefits of the VERA-2 approach are discussed in the chapter.
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A discussion of logical syllogisms and Venn diagrams. http://www.philosophypages.com/lg/e08a.htm
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Pressman, D.E. (2016). The Complex Dynamic Causality of Violent Extremism: Applications of the VERA-2 Risk Assessment Method to CVE Initiatives. In: Masys, A. (eds) Disaster Forensics. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-41849-0_10
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