Immigrant Earnings Distributions and Earnings Mobility in Canada: Evidence for the 1982 Landing Cohort from IMDB Micro Data
Bibliographic record
Abstract
This paper provides preliminary results from the IMDB panel database on the earnings distribution and earnings mobility of Canadian immigrants over their first post-landing decade in Canada. In this study we examine only the 1982 landing cohort of immigrants and follow them through to 1992. We examine earnings outcomes by four immigrant admission categories (independent economic immigrants, family class immigrants, and refugees) and separately for men and women. We find that there was indeed a substantial increase in the real earnings of 1982 immigrants over their first ten post-landing years in Canada. Annual earnings were initially highest for independent economic immigrants (all of whom are principal applicants) and lowest for refugees. But the growth rate of earnings was highest among refugees, so that by the tenth post-landing year refugees had the second-highest annual earnings levels after independent economic immigrants. Earnings inequality among immigrants in the 1982 landing cohort changed over the ensuing decade in a manner consistent with onward migration beyond Canada from the top end of the immigrant earnings distribution. In fact, sample attrition in the IMDB database was greatest among independent economic immigrants, followed by refugees. Earnings mobility was substantially greater for immigrants than for earners as a whole in the Canadian labour market, and declined with years since landing for both male and female immigrants. Earnings mobility was also greater among immigrant women than among immigrant men. The results indicate that the point system is effective in admitting higher-earning immigrants who succeed in moving ahead in the Canadian labour market, but suggest that onward (or through) migration among the most skilled immigrant workers may be a policy concern.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| 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) | 0.004 | 0.001 |
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".