Self-Employment Dynamics of Immigrants and Natives: Individual-level Analysis for the Canadian Labour Market
Bibliographic record
Abstract
This paper analyses the dynamic transitions of self-employment in four states of the Canadian labour market (paid-employment, self-employment, unemployment, and being out of the labour force) by answering three core questions: (1) What are the determinants of the transitions into and out of the four labour market states? (2) Are the probabilities of transitions between immigrants and natives significantly different, and if so, are they due to entry–exit rate gaps between immigrants and natives? (3) What are the proportions of spurious and structural state dependence in the labour market states of immigrants and natives? Our analysis was based on longitudinal data from Canada’s Survey of Labour and Income Dynamics (SLID) for males aged 25 to 55 for the period 1993 to 2004. Our results revealed that immigrants rather than natives are relatively more likely to be self-employed during the unemployment period. The findings also confirmed that males with positive investment income or wealth tended to be largely self-employed. From a policy perspective, the government provision of financial support towards self-employment positively benefits natives in seeking self-employment opportunities. Government policies to lessen labour market discrimination promotes the self-employment of immigrants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".