Impact des transferts de fonds des migrants sur les dépenses de santé des ménages recipiendaires au Togo
Bibliographic record
Abstract
Cet article vise à analyser l'effet des transferts des fonds des migrants sur les dépenses de santé des ménages récipiendaires au Togo. Les conséquences des flux migratoires de ces dernières années dans les pays en développement n'épargnent pas le Togo. On s'interroge sur les effets que ce phénomène peut avoir sur le quotidien des ménages. Pour atteindre cet objectif, nous nous sommes servis du modèle d'appariement par score de propensions en utilisant les données de l'enquête du questionnaire unifié des indicateurs de base de bien-être réalisée en 2015. Les résultats montrent que les transferts de fonds impactent positivement le recours aux services de santé modernes plutôt que traditionnels et ceux-ci impactent positivement aussi l'utilisation des services de santé publics. Une des recommandations majeures de nos résultats milite donc en faveur d'une facilitation des procédures de transferts de fonds des migrants au Togo.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".