Morbidité Des Enfants En Zones Urbaines Africaines. Le Cas De L’observatoire De Population De Ouagadougou (Burkina Faso)
Bibliographic record
Abstract
Rapid urbanization and its consequences in regard to access to water, sanitation, and waste management in African cities can be synonymous to health problems. Based on the data obtained from the Ouagadougou Health and Demographic Surveillance System, this paper focuses on characterizing most of those at risk of disease (fever, diarrhea, cough, infections of the skin and eyes). Spatial analysis show that populations in formal (zoned) neighbourhoods, compared to those in informal neighbourhoods, are most at risk of disease. However, in performing multiple correspondence factor analysis and classification, we found that the informal neighbourhoods are mostly at risk of disease. The formal and informal opposition is not absolute, but the differences remain strong despite the existence of atypical neighbourhoods. The contribution of the paper is to provide a new perspective for thinking in regards to the links between environment and children’s health.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".