Global Prison Health Care Governance and Health Equity: A Critical Lack of Evidence
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
The large and growing population of people who experience incarceration makes prison health an essential component of public health and a critical setting for reducing health inequities. People who experience incarceration have a high burden of physical and mental health care needs and have poor health outcomes. Addressing these health disparities requires effective governance and accountability for prison health care services, including delivery of quality care in custody and effective integration with community health services.Despite the importance of prison health care governance, little is known about how prison health services are structured and funded or the methods and processes by which they are held accountable. A number of national and subnational jurisdictions have moved prison health care services under their ministry of health, in alignment with recommendations by the World Health Organization and the United Nations Office on Drugs and Crime. However, there is a critical lack of evidence on current governance models and an urgent need for evaluation and research, particularly in low- and middle-income countries.Here we discuss why understanding and implementing effective prison health governance models is a critical component of addressing health inequities at the global level.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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