The Effect of Enclave Residence on the Labour Force Activities of Immigrants in Canada
Bibliographic record
Abstract
It has been well documented that immigrants' clustering of residence in large cities has been associated with the creation of a number of ethnic enclaves. The intensive exposure to own-ethnic population could affect immigrant labour market involvement positively or negatively. However, no extant Canadian research has provided empirical evidence on the sign of these enclave effects. In this paper, I use the 1981-2001 Censuses to estimate the impact of residence in ethnic enclaves on male immigrants' labour force participation rate and employment probability. For recent immigrants who arrived in Canada within the preceding ten years, the intensity of enclave residence is negatively associated with their labour force participation rate, but positively related to their employment probability in all censuses. However, living in an enclave has no significant effect on the labour force activity of older immigrants who have lived in Canada for more than twenty years. Since immigrants could be attracted to areas with more job opportunities and hence enlarge the size of an enclave, the estimated effects from probit regressions might be positively biased. I then use instrumental variable (IV) method to address this endogeneity problem, and the IV estimates are consistent with the probit regression results.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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 | 0.000 |
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".