Background and Preparatory Behaviours of Right-Wing Extremist Lone Actors: A Comparative Study
Bibliographic record
Abstract
<div><div><div><div><p>The threat posed by lone actors ranks high on the list of terrorism-related security concerns. In recent years especially, discussions about these perpetrators have focused primarily on those associated with, or inspired by, Islamic State and other jihadist entities. However, a significant portion of lone actors actually hail from right-wing extremist milieus. This article serves to draw attention to this subcategory of lone-actor terrorists, with a particular focus on their backgrounds and pre-attack behaviours. To that end, two datasets are presented that allow a comparison to be made between right-wing extremist lone actors and other ideologically-motivated lone actors. While several differences are noted, perhaps the most surprising finding is the degree of similarity between right-wing extremist lone actors and those adhering to different ideological currents. The results contribute to a knowledge-base that can inform discussion about whether risk assessment tools and protocols should differentiate between ideological categories of lone actor terrorists.</p></div></div></div></div>
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".