Radicalization as Martialization: Towards a Better Appreciation for the Progression to Violence
Bibliographic record
Abstract
The process whereby individual terrorists radicalize into violent extremism is typically understood as involving a series of individual mechanisms (e.g., grievance, attachment to friends, thrill), group processes (e.g., competition, social cohesion), and mass-public mechanisms. In this article, we demonstrate that this process is actually better understood as one of “martialization,” applicable to varying degrees to conventional and unconventional soldiers alike. We detail these commonalties via an analysis of six key themes in the literature: a) a sense of vicarious injustice, b) a sense of belonging/identity, c) meaning, excitement, and glory, d) active recruitment, e) indoctrination, and f) group solidarity. Lastly, we suggest why scholars have previously been blind to these parallels. By not recognizing the similarities, we are missing out on the opportunity to mobilize our entire existing knowledge base (on conventional and unconventional soldiers) for creating useful policies for countering violent extremism.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.037 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".