The “origins” of Preventing/Countering Violent Extremism: a critical reinterpretation
Bibliographic record
Abstract
This article addresses a void in the history of Preventing/Countering Violent Extremism (P/CVE), whose origins are typically associated with “Islamist homegrown terrorism” in Europe circa 2005. Drawing on genealogical analysis and ethnographic fieldwork, I examine three cases from P/CVE’s pre-history: (1) Dutch security reports beginning in the 1990s conceiving of a “radicalisation process” and multisector prevention; (2) early models in the US depicting the stages of “radicalisation”; and (3) “pre-crime” interventions in Muslim-majority countries that employ similar concepts. I argue that these cases, which have no recorded connection to each other, provide the template for the anticipatory and therapeutic “all-of-society” counter-terrorism approach embodied in P/CVE. I thus challenge the perception that P/CVE originated as a spontaneous and necessary reaction to the “homegrown” incidents in Europe. My investigation raises new questions over P/CVE’s Islamophobic legacy as well as how P/CVE’s turn towards viewing the targets of counter-terrorism as beneficiaries rather than adversaries, as indicated in its pre-history, buoyed the international growth of the field and its expansion across different “types” of violent extremism. The antecedents I explore also call attention towards P/CVE having a sociopolitical function that extends beyond public safety towards suppressing anticipated threats to western sociopolitical orders.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".