Changing Immigrant Characteristics and Pre-Landing Canadian Earnings: Their Effect on Entry Earnings over the 1990s and 2000s
Bibliographic record
Abstract
During the 1990s and 2000s, the characteristics of new immigrants to Canada changed significantly across several dimensions, including education, admission class, source region, and pre-landing Canadian work experience, owing at least partly to changes in immigration selection policies. This article examines whether these changes affected earnings trends among immigrants. Among all new immigrants and economic principal applicants, aside from cyclical fluctuations, entry earnings changed little over the 1990s and 2000s. This stability was the result of competing influences, some that tended to increase earnings and some that tended to reduce them. The key changes in immigrant characteristics that put upward pressure on entry earnings were the rising educational attainment in the 1990s and a large increase in the share of immigrants with high pre-landing Canadian earnings during the 2000s. The latter characteristic also accounted for the earnings advantage of provincial nominees over skilled worker immigrants. The policy implications of the results are discussed.
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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 | 0.001 | 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".