Sun-Smart Practices Amongst School Students (Grades 5, 7, and 9) in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to assess the current knowledge children possess on melanoma and sun-protective behaviour. METHODS: A one-page survey was administered to students in grades 5, 7, and 9. RESULTS: Three hundred ninety-two students from 11 schools in Edmonton were surveyed. Seventy-one percent of students knew that sun exposure can cause skin cancers. Sixty-nine percent were taught by their parents about sun protection, but only 44% of students received similar instructions from teachers. Twenty percent of students indicated that they never or rarely wore sunscreen. Twenty-five percent of students had experienced painful sunburns, and only 46% were willing to use sunscreen if it were available at school. More Caucasian students reported painful or peeling sunburns in each grade level than their non-Caucasian peers (for grade 5, P = .003; for grade 7, P < .0001; for grade 9, P = .001). For all grade levels, the percentage of Caucasian students who indicated that they would not wear sunscreen when going out in the sun was greater than among their non-Caucasian peers (for grade 5, P < .001; for grade 7, P = .003; for grade 9, P = .015). CONCLUSIONS: A comprehensive and focused approach to sun-smart education is recommended for students.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".