Croissance, inégalités et pauvreté : le cas des immigrants au Canada
Bibliographic record
Abstract
Using census data from 1991 to 2006, we analyze the dynamic of inequality and poverty among immigrants in Canada. Our results show that these immigrants have seen their economic situation deteriorate and dynamics of low income, poverty traps and major inequalities persist in successive cohorts. Despite a level of education increased, the return to human capital has decreased between 1996 and 2006. Like most immigrants derive most of their income from the labor market, employment levels and wage distribution play a role in income distribution and economic welfare of immigrants À l'aide des données de recensement de 1991 à 2006, nous analysons la dynamique de l'inégalité de revenu et de la pauvreté des nouveaux immigrants au Canada. Nos résultats montrent que les nouveaux immigrants ont vu leur situation économique se détériorer et une dynamique de faible revenu, de « trappes à pauvreté » et d'inégalités importantes persiste chez les cohortes successives. Malgré un niveau de scolarité en hausse, le rendement de leur capital humain a diminué entre 1996 et 2006. Comme la plupart des immigrants tirent la plus grande partie de leur revenu du marché du travail, les niveaux d'emploi et la répartition des salaires jouent un rôle primordial dans la répartition du revenu et le bien-être économique des immigrants
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".