Bibliographic record
Abstract
How do international differences in labor market institutions affect the nature of immigrant earnings assimilation? Using 1980/81 and 1990/91 cross-sections of census data from Australia, Canada, and the United States, we estimate the separate effects of arrival cohort and duration of destination-country residence on immigrant outcomes in each country. Relatively inflexible wages and generous unemployment insurance in Australia suggest that immigrants there might improve themselves primarily through employment gains rather than wage growth, and we find empirically that employment gains explain all of the labor market progress experienced by Australian immigrants. Wages are less rigid in Canada and the United States than in Australia, with the general consensus that the U.S. labor market is the most flexible of the three. We find that wage assimilation is an important source of immigrant earnings growth in both Canada and the United States, but the magnitude of wage assimilation is substantially larger in the United States. These same general patterns remain when we replicate our analyses for two subsamples of immigrantsEuropeans and Asiansthat are more homogeneous in national origins yet still provide sufficiently large sample sizes for each country.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.427 | 0.317 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".