Propensity of Canada's Foreign‐born to Claim Unemployment Insurance Benefits
Bibliographic record
Abstract
This article examines the relationship between claiming unemployment insurance benefits in Canada and the immigrant class under which immigrants were admitted (namely skilled workers, assisted relatives, family class, refugees), using a new data set that combines income tax and immigration records. Claims rates (or the proportion of immigrants who claimed unemployment insurance benefits) are calculated for each immigrant landing class for the cohorts of immigrants who landed in 1980, 1985 and 1989; for each cohort, annual claims rates are presented from the year after landing to 1995. The claims rates indicate that there are significant differences among the different immigrant landing classes: those admitted as skilled workers have relatively low claims rates, those in the family class or assisted relatives have higher rates, and refugees have the highest rates. For all immigrant landing classes, claims rates rise rapidly during the two or three years after arrival in Canada, but decline thereafter for all classes. Differences in claims rates on unemployment insurance benefits remain across the immigrant landing classes after general economic conditions and some characteristics of the immigrants are controlled.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".