Action Schools! BC: a socioecological approach to modifying chronic disease risk factors in elementary school children.
Bibliographic record
Abstract
BACKGROUND: Childhood physical inactivity and obesity are serious public health threats. Socioecological approaches to addressing these threats have been proposed. The school is a critical environment for promoting children's health and provides the opportunity to explore the impact of a socioecological approach. CONTEXT: Thirty percent of children in British Columbia, Canada, are overweight or obese, and 50% of youths are not physically active enough to yield health benefits. METHODS: Action Schools! BC, a socioecological model, was developed to create 1) an elementary school environment where students are provided with more opportunities to make healthy choices and 2) a supportive community and provincial environment to facilitate change at the school and individual levels. CONSEQUENCES: The environment in British Columbia for school- and provincial-level action on health behaviors improved. Focus group and project tracking results indicated that the Action Schools! BC model enhanced the conceptual use of knowledge and was an influencing factor. Political will and public interest were also cited as influential factors. INTERPRETATION: The Action Schools! BC model required substantial and demanding changes in the approach of the researchers, policy makers, and support team toward health promotion. Despite challenges, Action Schools! BC provides a good example of how to enhance knowledge exchange and multilevel intersectoral action in chronic disease prevention.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".