The Shift in Canadian Immigration Composition and its Effect on Wages
Bibliographic record
Abstract
We document recent changes in Canadian immigration, marked by an increasing prevalence of temporary residency. Using microdata from Statistics Canada's Labour Force Survey, we show that temporary workers' characteristics and nominal wages have diverged from those of Canadian-born workers. Between 2015 and 2024, temporary workers have become younger, less experienced and more likely to migrate from lower-income countries. As well, the shares of temporary workers in skilled occupations have declined moderately. Throughout this period, the average nominal wage gap between temporary and Canadian-born workers has more than doubled, widening from -9.5% to -22.6%. Further, we estimate Mincer regressions to assess how these evolving characteristics have contributed to the growing wage gap. Our findings show that this increase can be explained by observable characteristics. Our results suggest that aggregate nominal wages would have been, on average, 0.7% higher in 2023–24 had the characteristics of temporary workers remained unchanged over the past decade.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".