The Labour Market Adjustment Of Foreign-Born Workers In Canada: A Multinomial Logit Model Of Employment Status
Bibliographic record
Abstract
This paper examines how the employment profile of newcomers to Canada differs from that of the native-born, controlling for human capital and other individual characteristics, and whether that profile converges to that of the native-born as the length of residence in Canada increases. These questions are important for understanding whether (and the extent to which) foreign workers adjust to Canadian labour markets. They also have significant policy relevance, given that demographic trends in the country suggest that immigration will likely be an even more significant contributor to labour force growth in the years ahead. The econometric tool we employ is the multinomial logit model, which is estimated using data from the 2001 Census of Canada. Employment status, which is a categorical variable with several dimensions, is explained in terms of human capital, demographic and other individual characteristics, with additional controls for immigration status and variables intended to capture the impact of the length of residence of foreign workers in Canada. Since foreign workers are themselves a disparate group, entering Canada with very different socio-economic characteristics, with the potential for very different paths of subsequent adjustment to host country labour markets, we consider several foreign-born groups. This is important for capturing differences that reflect the shift in immigration away from traditional sources (e.g. the U.K) to non-traditional sources (e.g. Asia), and the implications for labour market activity and outcomes.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".