La féminisation de chefs de ménage à Haïti
Bibliographic record
Abstract
L’objectif de cet article était de dresser le profil des femmes cheffes de ménage et analyser les facteurs associés à ce phénomène à Haïti. Les données exploitées dans le cadre de ce travail de recherche proviennent des enquêtes démographiques et de santé réalisées à Haïti en 1994 et 2017 par l’Institut Haïtien de l’Enfance. L’analyse des données a été faite à deux niveaux : un niveau descriptif et un niveau explicatif multivarié à travers des modèles de régression multiniveaux. Les résultats ont révélé des changements au niveau du profil des femmes cheffes de ménage entre 1994 et 2017. De plus, il ressort que le milieu de résidence, l’âge, le niveau d’instruction, la taille du ménage et le niveau de vie sont les facteurs associés à la féminisation de chefs de ménage à Haïti.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".