Intégration économique des nouveaux immigrants: adéquation entre l'emploi occupé avant l'arrivée au Québec et les emplois occupés depuis l'immigration
Bibliographic record
Abstract
Résumé. Le manque de reconnaissance des titres de compétences acquis à l’étranger par les employeurs canadiens est l’une des causes souvent citées pour expliquer l’augmentation de la disparité salariale entre immigrants et non-immigrants au Canada. Le but de la présente étude est d’analyser le lien entre le domaine de l’emploi principal occupé par les immigrants avant leur arrivée et les emplois qu’ils ont occupés en début d’établissement, ainsi que l’effet net d’une adéquation des emplois sur le revenu des immigrants récents. Les données proviennent de l’enquête longitudinale sur l’établissement des nouveaux immigrants (ÉNI), laquelle retrace le parcours d’une cohorte d’immigrants arrivés en 1989. Les résultats suggèrent que la plupart des immigrants récents ne se trouvent pas un emploi dans leur domaine; par ailleurs, se trouver un emploi dans son domaine mène à un salaire plus élevé. Abstract. One of the reasons often provided for the salary gap between immigrants and native-born Canadians is the difficulty experienced by many immigrants in securing recognition for skills acquired overseas. In this paper, we examine the extent to which, after arrival, immigrants find jobs in the same occupations in which they were employed in their home countries. We also examine the effect on earnings of a match between the pre- and post-immigration occupations. The data come from the longitudinal survey “Établissement des nouveaux immigrants” which followed a cohort of immigrants who arrived in 1989. Our results suggest that most recent immigrants move into a new occupation when they arrive in Canada and that those whose pre- and post-immigration occupations match tend to earn more.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".