The use of legal empowerment to improve access to quality health services: a scoping review
Bibliographic record
Abstract
This paper presents the results of a scoping review that examines the extent to which legal empowerment has been used as a strategy in efforts to improve access to quality health services in low- and middle-income countries. The review identifies lessons learned regarding legal empowerment program strategy, as well as impact on health empowerment and health outcomes, research gaps, areas of consensus and tension in the field.The review included three main sources of data: 1) peer-reviewed literature, 2) grey literature, and 3) interviews with key legal empowerment stakeholders. Peer-reviewed and grey literature were identified via keyword searches, and interviewees were identified by searching an organizational database and snowball sampling.The key findings were: first, there is very limited documentation on the use of legal empowerment strategies for improving health services. Second, the legal empowerment approach tends to be focussed on issues that communities themselves prioritize, often narrowly defined local challenges. However, legal empowerment as a strategy that pursues collective and individual remedies has the potential to contribute to structural change. Third, for this potential to be realised, legal empowerment entails building capacity of service providers and other duty bearers on health and related rights. Finally, the review also highlights the importance of trust-trust in state institutions, trust in the paralegals who support the process and trust in the channels of engagement with public authorities for grievance redress.Several gaps also became evident through the review, including lack of work on private health providers, lack of discussion of the 'empowerment' effects of legal empowerment programs, and limited exploration of risk and sustainability. The paper concludes with a caution that practitioners need to start with the health challenges they are trying to address, and then assess whether legal empowerment is an appropriate approach, rather than seeing it as a silver bullet.
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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 | 0.073 | 0.216 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.026 | 0.029 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".