Thinking Beyond Extremism: A Critique of Counterterrorism Research on Right-Wing Nationalist and Far-Right Social Movements
Bibliographic record
Abstract
Abstract Researchers increasingly use counterterrorism approaches to explain how right-wing groups mobilize as a growing social movement. I reveal the limits of security-oriented research for studying right-wing movements using a semi-ethnographic case study of the Canadian yellow vests. Dominant security narratives paint Canada’s yellow vests as foremost a criminogenic and violent white nationalist movement. My findings, however, suggest that these groups (1) fetishize law and order; and (2) attempt to maintain legitimacy by rejecting vigilantism and policing extreme messaging. Fixating on the ‘extremism’ and criminal risks of right-wing movements can distort analysis and exaggerate their distance from mainstream culture. My data include over 40 h of participant-observation at 20 right-wing rallies and 35 interviews with current leaders and members of on-the-ground nationalist groups.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".