A Systematic Review of Randomized Controlled Trials of Interventions to Improve the Health of Persons During Imprisonment and in the Year After Release
Why this work is in the frame
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Bibliographic record
Abstract
We systematically reviewed randomized controlled trials of interventions to improve the health of people during imprisonment or in the year after release. We searched 14 biomedical and social science databases in 2014, and identified 95 studies. Most studies involved only men or a majority of men (70/83 studies in which gender was specified); only 16 studies focused on adolescents. Most studies were conducted in the United States (n = 57). The risk of bias for outcomes in almost all studies was unclear or high (n = 91). In 59 studies, interventions led to improved mental health, substance use, infectious diseases, or health service utilization outcomes; in 42 of these studies, outcomes were measured in the community after release. Improving the health of people who experience imprisonment requires knowledge generation and knowledge translation, including implementation of effective interventions.
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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 | 0.113 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it