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Toward a scientific approach to identifying and understanding indicators of radicalization and terrorist intent: Eight key problems


Journal abstract

Comments on the original articles by Meloy, Roshdi, Glaz-Ocik, & Hoffmann (see record 2016-18836-002), by Böckler, Hoffmann, & Zick (see record 2016-18836-003), by Meloy, Habermeyer, & Guldimann (see record 2016-18836-004), and by Van Der Meer (see record 2016-18836-005). Collectively, the articles contained in this issue offer a lot of interesting and insightful material on radicalization/violence indicators and the validity of the Terrorist Radicalization Assessment Protocol–18 (TRAP-18). They do this through testing the tool against a medium-sized sample of 22 cases (Meloy, Roshdi, Glaz-Ocik, & Hoffmann, 2015), and individual case studies ranging from the very famous (Breivik in the work of Meloy, Habermeyer, & Guldimann, 2015), to the not so famous (“U” in the work of Böckler, Hoffmann, & Zick, 2015), to the barely remembered (Lucheni in the work of Van Der Meer, 2015). They make important methodological contributions (discussions surrounding intercoder reliability) and substantive contributions in terms of new data generation and providing granular level detail on a couple of largely overlooked and unstudied cases. The results illustrate that time and again, various distal and proximal indicators built into the TRAP-18 were apparent. However, in a very short space of time, the empirical study of terrorist behavior has made some large steps with multiple data-driven, methodologically rich projects producing a lot of insight. The literature is finally at a point at which data access is not as much of a problem as it was previously. The next big challenges are essentially conceptual, and hopefully this commentary can work toward synthesizing and standardizing approaches across these multiple data-driven endeavors. To progress, we need to think more carefully about base rates, protective factors, weighting/clustering risk factors, thinking about the “terrorist” in a more nuanced way, and taking temporality into account.

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