Individual and community-level determinants of retention of Anglophone and Francophone immigrants across Canada
Bibliographic record
Abstract
This paper uses Cox Proportional Hazards Models, the Longitudinal Immigration Database, and Harmonized Census Data files to investigate the individual and community determinants of retention of Anglophone and Francophone immigrants in Canada among 1990, 1995, 2000 and 2005 landing cohorts in the first five years after landing. We focus on both the official language capacity of immigrants and the linguistic composition of the communities in which they settle. We find that Official Language Minority Communities (OLMCs) successfully retained Francophone immigrants better than non-OLMCs outside of Quebec. We also find that most cohorts of Anglophone immigrants are more likely to exit Quebec if they started out in an OLMC than if they did not.Cette étude utilise des modèles à risque proportionnel de Cox, la base de données longitudinales sur l’immigration, des fichiers de données harmonisés des recensements de la population afin d’examiner les déterminants au niveau individuel et communautaire sur la rétention à l’arrivée au pays des cohortes admises en 1990, 1995, 2000 et 2005 au cours des cinq premières années après leur établissement. L’accent de l’étude porte sur la capacité linguistique dans les deux langues officielles des nouveaux arrivants et la composition linguistique des communautés d’accueil. L’étude révèle que les communautés de langue officielle en situation minoritaire (CLOSM) ont plus de succès à maintenir les immigrants francophones que les communautés de langue officielle en situation majoritaire hors-Québec. L’étude révèle aussi que la plupart des cohortes anglophones sont plus susceptible de quitter le Québec si initialement établies dans une CLOSM.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".