Towards universal health care coverage in low- and middle- income countries: integrating refugees into national health systems
Bibliographic record
Abstract
diseases, notably mental health conditions, and injuries including those linked to gender-based violence (GBV).As many governments embark on health reforms towards achieving the Sustainable Development Goals, in particular universal health coverage (UHC), there is a growing need for sustainable and comprehensive approaches that can provide adequate financial risk protection and access to quality essential health care for all.Historically health services for refugees have often been provided through separate, parallel systems, particularly in refugee camps, but there is increasing recognition that such a model is unsustainable and leads to missed opportunities to benefit both refugee and host populations.As described in one of the papers in this supplement (Elnakib et al.) the integration of refugees within national health systems has emerged as a major element of humanitarian policies set out in recent the United High Commissioner for Refugees (UNHCR) and World Bank policy statements [3,4], and sometimes referred to as the "humanitarian-development nexus".More recently the World Health Organization (WHO) global action plan 2019-2023 on promoting the health of refugees and migrants explicitly notes the need to strengthen the provision of a variety of health services for refugees as part of UHC and "leaving no one behind" [5].During all phases of an emergency, but particularly during the post-emergency phase of a crisis, integrating refugees into health systems offers a number of benefits.For example, it has the potential to: (1) provide more Conflict and Health
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".