Availability of tanning salons in Ontario relative to indoor tanning policy (2001–2017)
Bibliographic record
Abstract
Ultraviolet (UV) radiation from indoor tanning equipment is a known cause of skin cancer; however, little is known about how the availability of indoor tanning salons has been impacted by indoor tanning legislation, including Ontario's Skin Cancer Prevention Act: Tanning Beds (SCPA). Tanning salon listings were obtained from the 2001 to 2017 editions of InfoCanada's Ontario Business to Business Sales and Marketing directories. Using descriptive statistics and regression analysis, we assessed the number of tanning salons before and after: 1) the 2006 International Agency for Research on Cancer (IARC) report on indoor tanning and skin cancer; 2) the 2009 World Health Organization (WHO) reclassification of artificial UV radiation as carcinogenic; and 3) the passing and enactment of Ontario's SCPA in 2013 and 2014, respectively. There were fewer tanning salon listings in the years after vs. before the IARC report, the WHO reclassification, and the passing and enactment of the SCPA. The number of tanning salons in Ontario, Canada has been declining since 2006, which may reflect a decline in indoor tanning bed use. Key public health policy instruments, including legislation and public education, appear to be associated with this trend, suggesting they may contribute to deterring indoor tanning.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".