Which Child Immigrants Face Earnings Disparity? Age‐at‐immigration, Ethnic Minority Status and Labour Market Attainment in Canada
Bibliographic record
Abstract
Abstract Using Canadian Census microdata from 1990 to 2005, we investigate the earnings attainment of immigrants to Canada in 6 age‐at‐arrival cohorts. In comparison to past work we extend our understanding regarding three dimensions of the age at immigration debate: we explore heterogeneity across fine grained age‐at‐arrival cohorts, over a fifteen‐year period and across different ethnic groups. We find that white immigrants and female immigrants arriving in Canada prior to age 18 face little earnings disparity. In contrast, visible minority male immigrants face significant earnings disparity regardless of their age‐at‐migration, and additionally this disparity increases sharply with age‐at‐migration. We find a break in earnings attainment at an age‐of‐arrival of 17, with immigrants arriving after this age performing much worse than those arriving at this age or earlier. The patterns observed are found for visible minority immigrants as a whole, and for Chinese, South Asian and African/Black origin immigrants examined separately.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".