Evaluation of Food Safety Practices at Louisiana Summer Feeding Sites and Food Safety Communication via Social Media During Crises
Bibliographic record
Abstract
The United States Department of Agriculture’s Summer Food Service Program (SFSP) provided children under the age of 18 in low-income areas 145 million free meals in 2018 through summer feeding sites. Food safety issues arise for Louisiana feeding sites due to time-temperature controlled foods served, weather patterns in Louisiana, seasonal staff and short operation time, and lack of equipment. The purpose of this study was to assess food safety practices at Louisiana feeding sites through observational study with intention to compare food practices at institutional and noninstitutional sites. A rubric following USDA food safety guidelines based on categories: hot holding, cold holding, cross contamination prevention, personal hygiene, and cleaning was developed for observations. Data obtained during observations (n=22) was compiled to determine frequent practices. Sixteen institutional and six noninstitutional sites were observed. Common violations include lack of temperature checking, lack of proper equipment, and personal hygiene. Noninstitutional sites all had improper holding, mostly due to lack of equipment. This study demonstrated the need for targeted food safety educational materials. The COVID-19 pandemic put the food system on alert and identified food safety as an important pillar in this crisis. Popular media is used as a disseminator of food safety information for public use; YouTube being one of the most highly trafficked websites on the internet. However, YouTube can contain misleading or untrustworthy information that contradicts validated information. This study evaluates food safety information circulated on YouTube during the COVID-19 pandemic. A video search on YouTube using the keywords “Food and COVID-19,” “Food safety and COVID-19,” and “Groceries and COVID-19” was conducted. In total, 85 videos from the U.S. and Canada were evaluated. More than half (59%) of videos presented handwashing procedures. Multiple and different produce washing procedures were also shown throughout videos. Food was not considered hazardous by 33% of the videos, but 20% mentioned that food packaging is potentially hazardous. Most videos had a host or guest who was a healthcare professional or professor/expert in their field. These findings demonstrate the need to develop educational interventions that increase awareness of social media as a tool for food safety dissemination.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".