Nutrition Education Across Gus Schumacher Nutrition Incentive Programs: A Landscape Analysis
Bibliographic record
Abstract
OBJECTIVE: To characterize the nutrition education landscape among Gus Schumacher Nutrition Incentive Program (GusNIP) projects to inform future evaluations of GusNIP. METHODS: Nutrition education activities provided by GusNIP-affiliated project sites were collected through annual data reports submitted via a secure web portal. A descriptive analysis was used to calculate frequencies and percentages for all variables (e.g., project site, nutrition education activities) to explore and compare nutrition education provided by GusNIP projects and sites (n = 93). RESULTS: Gus Schumacher Nutrition Incentive Program projects employed diverse nutrition education opportunities, including various venues, unique partnerships, and educational strategies, which differed across project and site types. CONCLUSIONS AND IMPLICATIONS: This paper characterizes the frequency and intensity of nutrition education offered within GusNIP and is an important step toward understanding, improving, and expanding nutrition education opportunities. Findings inform a future comprehensive evaluation across projects to understand the impact of reach, dose, and participant engagement in nutrition education and reveal important opportunities for program improvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".