Impact of Medical Legal Partnerships: A Scoping Review
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
Background Medical Legal Partnerships (MLPs) are collaborations between healthcare and legal services that aim to address the health-harming impacts of unmet legal needs. Better characterization of existing MLP models would be a resource for new and expanding MLPs to glean insight into challenges and opportunities to consider. This scoping review aimed to examine and map outcomes reported by MLPs. Methods MEDLINE, EMBASE, CINAHL, and the Index to Legal Periodicals databases were searched and studies reporting qualitative or quantitative outcomes of a MLP were eligible for inclusion. Independent dual review of titles, abstracts, and full-texts was conducted and the reported outcomes were analyzed. Results Thirty studies met inclusion criteria. Children and families were the most commonly served populations. The most frequently addressed legal needs pertained to housing, income, and personal/family stability. MLPs were associated with improved health, health services use, and legal outcomes. Education of healthcare professionals was associated with increased knowledge and confidence in addressing social needs. Discussion Overall, MLPs effectively partner healthcare and legal services to mitigate the health-harming consequences of unmet legal needs. MLPs facilitate access to care in legal circumstances that would otherwise exacerbate health conditions, and largely benefit communities that have been historically underserved by medical and legal systems.
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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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it