Author
Listed:
- Caitlin Clemmow
- Paul Gill
- Noémie Bouhana
- James Silver
- John Horgan
Abstract
Research suggests that lone-actor terrorists and mass murderers may be better conceptualized as lone-actor grievance-fueled violence (LAGFV) offenders, rather than as distinct types. The present study sought to examine the extent to which these offenders could (or could not) be disaggregated along dimensions relevant to the threat assessment of both. Drawing on a Risk Analysis Framework (RAF), the offending process was theorized as interactions among propensity, situation, preparatory, leakage and network indicators. We analyzed a dataset of 183 U.S. offenders, including sixty-eight lone-actor terrorists and 115 solo mass murderers. Cluster analysis identified profiles within each of the components: propensity (stable, criminal, unstable), situation (low stress, high stress (social), high stress (interpersonal)), preparatory (fixated, novel aggression, equipped, clandestine, predatory, preparatory), leakage (high leakage, low leakage), and network (lone, associated, connected). Bi-variate analysis examined the extent to which the profiles classified offenders previously labeled as lone-actor terrorists or mass murderers. The results suggest that while significant differences may exist at the periphery of these dimensions, offenders previously classified as lone-actor terrorists or mass murderers occupy a noteworthy shared space. Moreover, no profile classifies a single “type” of offender exclusively. Lastly, we propose a dynamic, interactional model of LAGFV and discuss the implications of these findings for the threat assessment and management of LAGFV offenders.
Suggested Citation
Caitlin Clemmow & Paul Gill & Noémie Bouhana & James Silver & John Horgan, 2022.
"Disaggregating Lone-actor Grievance-fuelled Violence: Comparing Lone-actor Terrorists and Mass Murderers,"
Terrorism and Political Violence, Taylor & Francis Journals, vol. 34(3), pages 558-584, April.
Handle:
RePEc:taf:ftpvxx:v:34:y:2022:i:3:p:558-584
DOI: 10.1080/09546553.2020.1718661
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