Redirected Radicals: Understanding the Risk of Altered Targeting Trajectories Among ISIL's Aspiring Foreign Fighters
Bibliographic record
Abstract
Since the formation of the Islamic State of Iraq and the Levant (ISIL) and its so-called Caliphate, the terrorist organization has demonstrated its capability and willingness to project force beyond its immediate area of operations in the Middle East, extending to Western countries. Rather than solely dispatching trained foreign fighters, in the United States, ISIL's strategy has involved homegrown violent extremists (HVEs) with a limited range of connectivity to the group. This thesis explores the threat posed by a subgroup of HVEs identified as redirected radicals, aspiring foreign fighters who, when prevented by counterterrorism actions from traveling overseas, decided instead to alter their targeting trajectory and commit violence in their home countries. Through an extensive comparative case study analysis of recent ISIL-related violent incidents and plots in the United States, Canada, and Australia, common trends identified the prevalence of redirected radicals. This thesis found that policy responses to this phenomenon differed significantly across these three nations, using an array of legal authorities including undercover investigations, passport revocation, and preventative detention with varying degrees of effectiveness. Ultimately, this thesis determined that investigations involving potential redirected radicals offer unique opportunities for counterterrorism authorities to effectively decrease the likelihood of a domestic attack.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".