Utilizing Social Media to Educate School Nutrition Professionals
Bibliographic record
Abstract
Background: Schools enrolled in United States Department of Agriculture (USDA) Team Nutrition (TN) projects often have positive outcomes and develop useful resources. The challenge was to find an accessible mean to share outcomes and resources with schools across Ohio. Purpose: The purpose of this project was to design a blog to educate school nutrition professionals and build awareness of positive activities related to Ohio school meals. This project also aimed to identify indicators of engagement, make recommendations for research and practice, and identify a set of best practices for future blog site use. Methods: The foundation of the blog (OHIOSmarterLunchrooms.com) was content development in the form of original content, resource materials, evaluation tools, and school nutrition research. Results: In the initial eight months, the blog generated 1,301 visitors, 3,277 views and 793 resource downloads. Agency partnerships were important drivers of traffic to the site. A quarter of all referrals were generated from the state department of education, and 14% from the USDA. A statewide taste test event was effective in reaching schools not enrolled in TN-funded projects. Most published content (24 of 28 posts) was original content. Contributor posts received the most user views, “likes,” and ratings. The most popular downloads were taste test event materials (43%), followed by professionally designed signs and posters (37%). Conclusion: Utilizing a blog for information dissemination among school nutrition professionals has proven to be a viable educational platform. Participation and engagement in OHIO Smarter Lunchrooms content continues to grow.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".