<i>Healthy Eating Champions Award</i> For Elementary Schools
Bibliographic record
Abstract
PURPOSE: The Healthy Eating Champions Award for Elementary Schools (HEC) is a public health initiative that recognizes and rewards schools for their outstanding commitment to the promotion of nutrition, for nutrition education, and for making healthy foods and beverages available. This process evaluation assessed HEC implementation, identified benefits and barriers, and solicited suggestions for program improvement. METHODS: In-person interviews with principals or their designates from 28 HEC participating schools were conducted in fall 2006. RESULTS: Participants had positive feelings about the HEC program and shared many success stories. Perceived program benefits included increased student awareness about healthy eating, more student involvement in healthy eating initiatives, the creation of opportunities for goal setting and spirit boosting, and improved hygiene practices. The challenge of getting parents and teachers involved and the significant financial needs of schools in low-income areas were identified as challenges. CONCLUSIONS: Participants view the HEC program as having a positive impact on the healthy eating environment in schools.
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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 | 0.003 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".