To Vape, or Not to Vape: Electronic Cigarettes and the Ambiguous State of Their Legality in Canada
Bibliographic record
Abstract
he legality of e-cigarettes remains ambiguous in Canada in terms of their use and sale.The question of legality is of relevance due to the widespread and increasing popularity of e-cigarettes.The purpose of this paper is to determine whether any definitive conclusions can be drawn regarding the legality of e-cigarettes in Canada.Deriving an answer to the issue of the legal status of e-cigarettes in Canada involved a careful dissemination of the applicable legislation, Parliamentary materials, Health Canada notices, scientific literature, and general media reports.Ultimately, primary emphasis was placed on applicable and potentially applicable federal legislation due to federal legislation being the only avenue for a comprehensive and national legislative framework for regulating e-cigarettes.The question of legality was approached from a purely legally substantive manner and questions of whether Parliament should or should not allow the use of e-cigarettes were * J.D. (2017).Editor's note: The research in this article is current as of August 2016.The author is aware that legislation to regulate vaping was introduced in the fall of 2016.See: Kristy Kirkup, "Federal Liberals' new vaping bill targets kids, smokers hoping to quit",
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.022 | 0.017 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".