Protection sociale des travailleurs du secteur informel au Cameroun : une analyse de la demande
Bibliographic record
Abstract
L’objectif de cet article est d’examiner la souscription des entrepreneurs du secteur informel au système public de protection sociale au Cameroun. L’analyse porte sur un échantillon de 4598 promoteurs d’unités de production informelle (UPI), issu de la 2nde phase de la deuxième enquête sur l’emploi et le secteur informel au Cameroun (INS, 2010). En s’inspirant de la revue de la littérature économique, les résultats économétriques obtenus à l'aide de l’estimation d’un modèle probit avec biais de sélection révèlent que les entrepreneurs du secteur informel seront moins enclins à adhérer à un système public de protection sociale offrant les prestations sociales ci-après: l’assurance vieillesse, l’assurance invalidité, l’allocation familiale et l’allocation maladie professionnelle.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".