Chapter 1 – Homegrown Terrorist Radicalization: The Toronto 18 in Comparative Perspectives
Bibliographic record
Abstract
Canadian concern with the domestic threat of religious terrorism came of age with the arrest of the members of the Toronto 18 in 2006. This chapter seeks to increase our understanding of this case by placing it in comparative perspective in three ways. First, by arguing that the Toronto 18 represents one of the purest instances of so-called “homegrown terrorism.” Second, by comparing the data available on the ten adults convicted with the data available on similar terrorists in Europe, the United Kingdom, and the United States. Findings are examined for age, ethnicity, socio-economic status, education, occupations, criminality, mental health, and family and religious background. Third, insights from two recent and comprehensive theories of the process of radicalization, Lorne Dawson’s “social ecology model” and Arie Kruglanski et al.’s “3 N model” are used to make better sense of what happened and why. In the end, however, much remains unclear because we still lack the appropriate data.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.019 | 0.027 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".