Health warning labelling practices on narghile (shisha, hookah) waterpipe tobacco products and related accessories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Waterpipe tobacco smoking prevalence is increasing around the globe despite current evidence that smoke emissions are toxic and contain carcinogenic compounds. OBJECTIVE: To evaluate current health warning labelling practices on waterpipe tobacco products and related accessories. METHODS: All waterpipe tobacco products, as well as waterpipe accessories, were purchased from Lebanon and a convenience sample was obtained from Dubai (United Arab Emirates), Palestine, Syria, Jordan, Bahrain, Canada, Germany and South Africa. FINDINGS: Of the total number of waterpipe tobacco products collected from Lebanon, the majority had textual health warning labels covering on average only 3.5% of total surface area of the package. Misleading descriptors were commonplace on waterpipe tobacco packages and related accessories. CONCLUSIONS: There are no WHO FCTC compliant waterpipe-specific health warning labels on waterpipe tobacco products and related accessories. Introducing health warnings on waterpipe tobacco products and accessories will probably have worldwide public health benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it