Foreign Terrorist Fighters from the North Caucasus: Understanding Islamic State Influence in the Region
Bibliographic record
Abstract
At the height of the influence of the 'Islamic State' in Syria, it involved in its ranks approximately 30,000 foreign fighters, with about a quarter of them coming form Russia (Chechnya and Dagestan) and the former Soviet Union. This article looks into the phenomenon of North Caucasian foreign terrorist fighters and its implications for security in North Caucasus, the Russian Federation and world-wide. The numbers of fighters returning from Syria to the region are not exactly known. Yet, upon returning home, the first wave of foreign fighters has managed to secure and build upon their reputations and expand their experience, skills and networks, establishing different jamaats and, in one instance, a 'jihadist private military company.' Given the opportunity, the second wave will most likely fight in the Caucasus, but if unable to return home they may be motivated to strike elsewhere.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".