Repartition initiale entre les entreprises et croissance des gains des immigrants
Bibliographic record
Abstract
Malgre le role que peuvent jouer les employeurs dans la selection des immigrants economiques, on en sait peu sur l'existence d'une association entre les caracteristiques au niveau de l'entreprise et les resultats des immigrants sur le marche du travail a long terme, ainsi que sur le mecanisme de cette association. En guise de premiere etape en vue de fournir des donnees pertinentes, la presente etude a pour but de determiner s'il existe des ecarts importants entre les gains initiaux des immigrants qui obtiennent leur premier emploi dans des entreprises a bas salaires et de ceux qui debutent dans des entreprises a hauts salaires, et si les ecarts initiaux entre les gains diminuent a mesure que s'allonge la periode de residence au Canada. l'etude vise aussi a savoir si, en termes de gains, le rendement du capital humain des immigrants est plus eleve s'ils obtiennent leur premier emploi dans des entreprises a hauts salaires que s'ils debutent dans des entreprises a bas salaires. Le present document s'appuie sur des donnees tirees de la Base de donnees canadienne sur la dynamique employeurs-employes (BDCDEE) creee par Statistique Canada.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".