Linguistic Proximity and the Labour Market Performance of Immigrant Men in Canada
Bibliographic record
Abstract
Abstract The ability to speak the language of the destination country plays a key role in the labour market performance of immigrants. To assess the influence of language on economic assimilation, we combine large samples of the restricted version of the Canadian Census (1991–2006) with both a measure of proximity to English of the most used language in the immigrant’s country of origin, and information about wages and the occupational skills required for the jobs immigrant men hold. Immigrant men whose language is more distant from English earn lower wages and work in jobs requiring more physical strength and fewer social and analytical skills, than the jobs of similar native‐born workers. More importantly, linguistic distance imposes a relatively larger wage penalty on college‐educated upon entry into the country than on non‐college educated individuals. However, both the wage and the analytical skill requirements of the jobs held by college‐educated immigrant men from linguistically distant countries increase markedly with time in the country, while their physical strength requirements decline moderately. Our analysis suggests that facilitating language acquisition may speed up the labour market assimilation of immigrant men in 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".