Creating a student-led health magazine with an urban, multicultural, resource-restricted elementary school: Approach, process and impact
Bibliographic record
Abstract
BACKGROUND: Health magazines effectively deliver health information. No data regarding student-led magazines to promote health exist. OBJECTIVE: To evaluate whether children's health knowledge, interests and lifestyle choices improve following distribution of a student-led health magazine. METHODS: Elementary students worked with teachers and paediatric residents to publish a health magazine. A healthy lifestyle challenge page promoted reduction in soda pop consumption. Pre- and poststudent questionnaires explored knowledge, interests and behaviours related to health. RESULTS: Sex and grade distributions were similar in pre- and post-questionnaires. Ninety-seven percent of children reported the magazine helped them learn about health. Pre- and postknowledge scores did not differ (P=0.36). Following distribution, the percentage of students who reported drinking no soda increased from 43% to 67% (P=0.004), and those who reported drinking <2 glasses of soda per day increased from 66% to 85% (P=0.01). CONCLUSIONS: A student-led health magazine was effective in motivating short-term student-reported behavioural change.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".