190: Banning Tanning
Bibliographic record
Abstract
The World Health Organization lists artificial tanning beds as a class one physical carcinogen. Tanning bed use is associated with a 75% increased risk of cutaneous malignant melanoma if used before the age of 35. In 2012, the Manitoba government announced a parental consent law that requires minors to have a guardian present or sign a permission form for children and youth to use artificial tanning equipment. This law falls below the national standards as set by the Canadian Pediatric Society (CPS); furthermore, parental consent laws have been shown to be ineffective at changing commercial tanning exposure in youth. Our group of senior pediatric residents worked on a project advocating for a complete ban of commercial tanning use for all youth under the age of 18 in Manitoba. The first component of the project focused on community education. Residents presented to middle and high school students about the harmful consequences of tanning, and created educational pamphlets that were made available at several general pediatric clinics. The second component of our project focused on legislative change and public forum advocacy. Residents engaged with the media to bring awareness to the general public about the risks of artificial tanning. A petition calling for a complete ban of artificial tanning for minors was also created. This petition, which included over 1000 signatures, along with evidence supporting a full ban for artificial tanning was presented to the Manitoba Ministers of Health and Healthy Living in an invited forum to advocate for legislative change. These efforts were successful and resulted in the recent proposed legislation calling for a full ban on artificial tanning for minors; this is expected to pass into Manitoba law in the spring of 2015. This project serves as an example of how physicians can promote the health of their patients via community education, collaboration with public health experts, and involvement in local government.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".