Are Minority Serving Institutions Contributing to Unhealthy Eating and Health Disparities Among College Students: A Pilot Study
Bibliographic record
Abstract
Dietary habits are developed through a combination of biological, environmental, socioeconomic, and psychosocial factors. However, these dietary habits can also be influenced by access and education. College undergraduate years are important for the development of life skills including the ability to select nutritious meals. This is of vital importance for students who are from communities that are classified as food desserts and food swamps, where positive nutrition behaviors may not be supported. The purpose of this pilot study was to assess the food options at two minority serving institutions in New Jersey to determine the amount of healthy options available. A content analysis was completed by assessing the menus of the selected dining services at the respective institutions and determining their health impact. Twenty-seven food establishments were analyzed. The food locations were categorized into healthy dining (7.4%), unhealthy dining (14.8%), healthy fast food (7.4%), unhealthy fast food (40.7%), healthy café (3.7%), unhealthy café (18.5%), healthy prepackaged (0%), and unhealthy prepackaged (7.4%). Healthy eateries made up 18.5% and unhealthy eateries made up 81.4% of the food offerings. This significant difference in healthy compared to unhealthy offerings is a call to action to improve food choices on the campuses of minority serving institutions. Chronic diseases continue to impact people of younger ages and contribute to health disparities. Colleges have a unique opportunity to positively influence the lifestyle behaviors that can decrease these chronic disease rates. Future studies should investigate the food options at minority serving institutions throughout the United States.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".