A community-based approach to indigent selection is difficult to organize in a formal neighbourhood in Ouagadougou, Burkina Faso: a mixed methods exploratory study
Bibliographic record
Abstract
BACKGROUND: In most African countries, indigents treated at public health centres are supposed to be exempted from user fees. In Africa, most of the available knowledge has to do with targeting processes in rural areas, and little is known about how to select the worst-off in an urban area. In rural communities of Burkina Faso, trials of participatory community-based selection of indigents have been effective. However, the process for selecting indigents in urban areas is not yet clear. METHODS: This study evaluates a community-funded participatory indigent selection process in both a formal (loti) and an informal (non-loti) neighbourhood in the urban setting of Burkina Faso's capital. This was an exploratory study to evaluate the processes and effectiveness of participatory targeting. We conducted individual interviews (n = 26) and analyzed secondary qualitative data (eight focus groups, 16 individual interviews). We also used the results of a socioeconomic survey (carried out by the Ouaga HDSS in 2011) of all the households established in the areas, including those of selected indigents. RESULTS: The coverage of indigent targeting was very low: 0.33% (loti) and 0.22% (non loti). In the non loti neighbourhood, the level of poverty among people selected was higher than the mean level of the poor who were not selected. Some indigents selected in the loti neighbourhood were not among the worst-off. The process was difficult to organize in the loti neighbourhood; people knew each other less well and were not very available, and there were cases of collusion. The process worked well in the non loti neighbourhood. CONCLUSIONS: This intervention research provides new evidence about the feasibility of a community-based selection process in an urban setting in Africa by comparing two different urban settings. The participatory community-based selection process appeared to be suitable for the non loti neighbourhood, but other targeting strategies need to be found for loti areas. Specific budgets need to be allocated to increase the coverage of indigent targeting.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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 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".