Enquête canadienne sur le tabac et la nicotine 2022
Bibliographic record
Abstract
L'Enquête canadienne sur le tabac et la nicotine (ECTN) de 2022 permet de mesurer la prévalence de la consommation de cigarettes, de produits de vapotage, de cannabis et d'alcool chez les Canadiens âgés de 15 ans et plus. Cette enquête est menée par Statistique Canada pour le compte de Santé Canada. La compréhension des tendances canadiennes en matière de consommation de tabac, de nicotine, de cannabis, de produits de vapotage et d'alcool est essentielle à l'élaboration, à la mise en œuvre et à l'évaluation efficaces des stratégies, politiques et programmes nationaux et provinciaux. La compréhension des tendances canadiennes relatives à la consommation de tabac, de nicotine, de cannabis et d’alcool est essentielle à l’élaboration, à la mise en œuvre et à l’évaluation efficaces des stratégies, politiques et programmes nationaux et provinciaux. L’ECTN a été menée par Statistique Canada à la fin de 2022 et au début de 2023, avec la coopération et le soutien de Santé Canada.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.032 | 0.009 |
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".