Improving Nutritional Wellness and Optimizing Health for Justice-Impacted Populations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Mass incarceration in the United States has led to significant public health challenges, with incarcerated individuals experiencing higher risks of nutrition-related chronic conditions, such as cardiovascular disease, hypertension, and diabetes. We reviewed the National Commission on Correctional Health Care’s recommendations for providing high-quality, culturally relevant foods and wellness programming in correctional settings to ensure the nutritional wellness of incarcerated individuals. The crucial role of registered dietitian nutritionists in facilitating such changes is also emphasized. Additionally, formerly incarcerated individuals continue to face food insecurity, chronic health issues, and insufficient resources, and require policy changes, advocacy, and education upon reentry into communities to ensure optimal health. Embedding National Commission on Correctional Health Care’s recommendations in correctional and community settings is essential for improving the health and well-being of justice-impacted individuals, highlighting the need for further research and policy reformation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 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 it