Entrepreneurs et Salariés en Algérie : application d’un probit bivarié par genre et par secteur
Bibliographic record
Abstract
En utilisant les micros donnees de l.enquete Emploi de l'Office National des Statistiques (Algerie) effectuee en 2003 aupres des menages, cette etude empirique porte sur l'effet des caracteristiques socioeconomiques de l'individu (education, experience professionnelle, situation matrimoniale, secteur d.activite, affiliation ou non a la securite sociale). Les resultats de ce travail montrent que le niveau educatif, l'experience professionnelle, l'emploi dans l'industrie et les services, ont respectivement des effets significatifs sur le fait d'etre entrepreneur ou salarie, pour les femmes et les hommes egalement. L'analyse comparative entre les femmes et les hommes montre que la correlation entre les deux termes d.erreurs du modele probit bivarie, nommee ρ, n'est pas egale a zero. Elle avoisine les 7%. Ce qui justifie l'utilisation d'un modele probit bivarie au lieu de deux modeles probit simples. Mots clefs : Algerie, genre, entrepreneurs
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".