The long-term economic integration of resettled refugees in Canada: a comparison of Privately Sponsored Refugees and Government-Assisted Refugees
Bibliographic record
Abstract
Private refugee sponsorship has been an important Canadian policy initiative for 40 years. It is now attracting international attention as Europe grapples with an influx of refugees. However, no Canadian research has evaluated the long-term refugee economic integration associated with private sponsorship, in comparison to government assistance, using rigorous multivariate analysis. This study compares the economic outcomes of Privately Sponsored Refugees (PSRs) with those of Government-Assisted Refugees (GARs) using the Longitudinal Immigration Database, administrative data on virtually all immigrants and refugees arriving in Canada since 1980. Our regression analysis finds PSRs maintain higher employment rates and earnings than GARs up to 15 years after arrival when measurable compositional differences between the two groups are adjusted. The PSR advantage is particularly noticeable among less educated refugees. The findings suggest unmeasured factors (e.g. effectiveness of settlement policies, refugee selection processes, societal reception of refugees) may partly explain PSRs’ long-term economic advantage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".