Immigrant Economic Integration: A Prospective Analysis over Ten Years of Settlement
Bibliographic record
Abstract
ABSTRACT The growing diaspora in migration has prompted Western countries in recent years to examine the factors contributing to the economic integration of newcomers. If their integration is unsuccessful, it could create economic inequalities and be burdensome to the host society. The inequalities experienced by working immigrants have often been examined through cross‐sectional data describing the situation at a specific moment in time, with limited consideration of the complexity of the immigrant's settlement experience. This paper examines the economic integration of new immigrants through prospective analysis and considers multiple factors concurrently in an effort to address some of this complexity. The current study focuses on employment disparities across source regions. The analyses are taken from a ten‐year longitudinal survey describing the socio‐economic experience of 429 new immigrants settled in the Montreal metropolitan area. Over time, wage and occupational mobility increase, although it appears stagnant for different groups of respondents from specific regions such as East Asia, North Africa and the Middle East. Also, like respondents from sub‐Saharan Africa, these respondents face difficulties sustaining a position in the labour market.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".