An act to amend the criminal code, the official secrets act, the Canada evidence act, the proceeds of crime (money laundering) act and other acts, and to enact measures respecting the registration of charities, in order to combat terrorism : Bill C-36, assented to 18th December, 2001 : statutes of Canada 2001, chapter 41 = Loi modifiant le code criminel, la loi sur les secrets officiels, la loi sur la preuve au Canada, la loi sur le recyclage des produits de la criminalité et d'autres lois, et édictant des mesures à l'égard de l'enregistrement des organismes de bienfaisance, en vue de combattre le terrorisme : project de loi C-36, sanctionné le 18 décembre 2001 : lois du Canada (2001), chapitre 41 [Recurso electrónico]
Bibliographic record
Abstract
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.033 | 0.016 |
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".