An Empirical Study of Terrorism Charges and Terrorism Trials in Canada between September 2001 and September 2018
Bibliographic record
Abstract
In order to provide clarity with respect to terrorism prosecutions in Canada, this paper offers a broad, empirical overview of what has taken place over the first fifteen plus years of terrorism prosecutions in Canada. Specifically, it consolidates for the first time all charges and criminal cases brought under Part II.1 of the Criminal Code from 2001 to September 2018, and provides the names of the accused, verdicts including the number of guilty pleas versus stays versus full trials, the conviction rates, and the charging trends and patterns. It also charts the demographics (gender) of the accused, the type (ideologies) of terrorism on trial in Canada, and other factors. Finally, it discusses some specific controversial topics in Canadian terrorism prosecutions, including the prosecution of foreign fighters and of right wing extremism as terrorism.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".