Beyond binary: Analyzing closed-source data to compare specific roles and behaviors within violent and nonviolent terrorist involvement.

Amber Seaward, Zoe Marchment, Caitlin Clemmow, Frank Farnham, Richard Taylor, Luc Taperell, Sara Henley, Sara Boulter, Karen Townend, Paul Gill
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Abstract

Increasingly, studies compare risk and protective factors for involvement in violent and nonviolent terrorist behaviors. This exploratory study investigates whether this distinction is sufficient, or whether it should be disaggregated further into more granular terrorist roles and behaviors. Using data on 404 referrals to a UK countering violent extremism Prevent hub specializing in mental health and associated needs, we compare violent and nonviolent referrals, and then more specific behaviors (vulnerability, proactive extremism, foreign fighting, and violence planning). Bivariate and multivariate analyses show there is value in disaggregating beyond the binary violence versus nonviolence distinction, as more (and more detailed) relationships emerged when using the disaggregated set of behaviors. While gender did not differentiate violent and nonviolent referrals, women were more likely to be referred for radicalization vulnerability or potential foreign fighting. Extreme right-wing and extreme Islamist referrals were no more or less violent overall, but Islamist referrals were disproportionately referred for both the most and least violent behaviors. Personality and developmental disorders were associated with violence, and disaggregated behaviors provided detailed insight into the drivers of these associations. These exploratory findings, while interesting, likely do not generalize beyond our specific sample. Instead, this study's value lies in demonstrating the utility for both research and, eventually, practice of disaggregating beyond violence and nonviolence. The results demonstrate clear operational implications for threat assessment in the need to include a more refined set of risk factors to aid in assessing risk of more relevant outcomes than terrorist involvement overall.

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超越二元对立:分析闭源数据,比较暴力和非暴力恐怖主义参与中的特定角色和行为。
越来越多的研究对参与暴力和非暴力恐怖主义行为的风险和保护因素进行了比较。这项探索性研究探讨了这种区分是否足够,或者是否应进一步细分为更细化的恐怖主义角色和行为。我们利用英国打击暴力极端主义预防中心的 404 个转介数据,比较了暴力和非暴力转介,以及更具体的行为(脆弱性、主动极端主义、对外战斗和暴力计划)。双变量和多变量分析表明,除了暴力与非暴力的二元区分外,还有其他分类价值,因为在使用分类行为集时,会出现更多(更详细)的关系。虽然性别并没有区分暴力和非暴力的转介,但女性更有可能因激进化脆弱性或潜在的对外战斗而被转介。极端右翼和极端伊斯兰教转介人员的暴力程度总体上并无高低之分,但伊斯兰教转介人员因最严重和最轻微的暴力行为而被转介的比例过高。人格障碍和发育障碍与暴力有关,而分类行为则提供了对这些关联驱动因素的详细了解。这些探索性发现虽然很有趣,但很可能不会超出我们特定样本的范围。相反,本研究的价值在于证明了对暴力和非暴力行为进行分类对研究和最终实践的实用性。研究结果对威胁评估具有明确的操作意义,即需要纳入一套更精细的风险因素,以帮助评估比参与恐怖活动更相关的风险。
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