Adventures in Regulation: Seeking to Define Efficacy for Natural Health Products in Canada
Bibliographic record
Abstract
Since January 1, 2004, natural health products have been regulated in Canada under the Natural Health Products Regulations. This presentation will educate the participant on the regulatory framework for NHPs in Canada and the regulatory tools used by Health Canada to make decisions respecting these products. The presentation will include a focus on the particular challenge of defining what is meant by efficacy with this product category. The presentation will draw on the more than six years of experience in Canada assessing the safety, quality and efficacy of these products and will reflect on a few recent examples involving specific ingredients and products. The presentation will also attempt to stimulate reflection around the question of efficacy, the value of clinical experience and the expectations of users of these products. Participants will gain knowledge on how the Natural Health Products Directorate has been innovative through the creation of pre-cleared information and collaboration with key stakeholders. These innovations have enabled Canada to issue product licenses to close to 23,000 natural health products.
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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 | 0.037 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".