Using livelihoods to support primary health care for South Sudanese refugees in Kiryandongo, Uganda
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
Introduction: Conflict in South Sudan has displaced 2.3 million people, of whom 789,098 (35%) have taken refuge in Uganda – a country that allows refugees to work, own property, start their own businesses and access public health services. In this context, refugees have identified livelihoods and primary health care as key priorities for their wellbeing. Objective: Building on previous research in South Sudan and Uganda, the objective of our current work is exploring how income-generating livelihood activities and other interventions can be used to support primary health care for South Sudanese refugees in Kiryandongo District, Uganda. Methods: We drew on existing secondary data and five scoping visits to the refugee settlements in Kiryandongo and northern Uganda to formulate our approach. Results: In Kiryandongo District, primary health care and livelihoods can best be supported by an integrated combination of 1) providing standardised training to local Village Health Teams (VHTs); 2) helping organise VHTs into village savings and loan association groups; and 3) supporting VHTs with training to establish sustainable income-generating activities. Conclusions: Integrated interventions that address income-generating activities for community health workers can meet the basic needs of front-line volunteer primary health care staff and better enable them to improve the health of their communities. Keywords: primary health care, refugees, livelihoods, South Sudan, Uganda, Kiryandongo
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it