Youth Access Laws
Bibliographic record
Abstract
OBJECTIVE: To compare laws governing youth access to UV irradiation at indoor tanning facilities with laws governing youth access to tobacco. DESIGN: Tobacco and UV irradiation youth access laws were assessed via correspondence with public health offices and computerized legal searches of 6 industrialized nations with widely differing skin cancer incidence rates. SETTING: National, provincial, and state legal systems in Australia, Canada, France, New Zealand, the United Kingdom, and the United States. PARTICIPANTS: Public health, legal, information science, and medical professionals and government and tanning industry representatives. MAIN OUTCOME MEASURES: Statutes specifying age restrictions for the purchase of indoor tanning services or tobacco products. RESULTS: The 5 English-speaking countries with common law-based legal systems unilaterally prohibit youth access to tobacco but rarely limit youth access to UV irradiation from tanning salons. Only very limited regions in the United States and Canada prohibit youth access to indoor tanning facilities: Texas, Illinois, Wisconsin, and New Brunswick prohibit tanning salon use by minors younger than 13, 14, 16, and 18 years, respectively. In contrast, French law allows minors to purchase tobacco but prohibits those younger than 18 years from patronizing tanning salons. CONCLUSIONS: Youth access laws governing indoor tanning display remarkable variety. Uniform indoor tanning youth access laws modeled on the example of tobacco youth access laws merit consideration.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".