© Canadian Journal of Regional Science/Revue canadienne des sciences régionales, XX:1,2 (Spring-Summer/Printemps-Été 1997), 29-48. Metropolis ISSN: 0705-4580 Printed in Canada/Imprimé au Canada Immigration and Poverty in
Bibliographic record
Abstract
For decades the abiding immigrant narrative in Canada and the other major receiving nations, including the United States and Australia, has been one of upward social mobility over time. This story has been registered by a large number of studies that have chronicled immigrant earnings, or more generally income (for reviews, Sloan and Vaillancourt 1994; Li 1996). While typically immigrants face an initial penalty in personal earnings, after a decade or so earnings move close to the national norm, though with certain important variations. When other controls are in place, immigrant men are penalised more than women relative to the national average, while some visible minorities face a considerable earnings shortfall (Pendakur and Pendakur1996). At the same time there is some evidence of worsening economic fortunes for immigrants in recent years, leading to the spectreof ‘diminishing returns ’ to the immigration programme in both Canada and the United States (DeVoretz 1995; Borjas 1995). At what point in this apparently deteriorating trajectory do immigrants then become a significant part of the growing poverty population in Canada with its
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.204 | 0.046 |
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".