The emergence of the national medical assistance scheme for the poorest in Mali
Bibliographic record
Abstract
Universal health coverage is high up the international agenda. The majority of the West Africa's countries are seeking to define the content of their compulsory, contribution-based medical insurance system. However, very few countries apart from Mali have decided to develop a national policy for poorest population that is not based on contributions. This qualitative research examines the historical process that has permitted the emergence of this public policy. The research shows that the process has been very long, chaotic and suspended for long periods. One of the biggest challenges has been that of intersectoriality and the social construction of the poorest to be targeted by this public policy, as institutional tensions have evolved in accordance with the political issues linked to social protection. Eventually, the medical assistance scheme for the poorest saw the light of day in 2011, funded entirely by the government. Its emergence would appear to be attributable not so much to any new concern for the poorest in society but rather to a desire to give the social protection policy engaged in a guarantee of universality. This policy nonetheless remains an innovation within French-speaking West Africa.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".