Bridges or Barriers? The Relationship between Immigrants’ Early Labor Market Adversities and Long-term Earnings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using data from the Extended Longitudinal Survey of Immigrants to Canada (LSIC-IMDB), this article investigates the association between early adverse labor market experiences in the host country and immigrants’ long-term earnings. We use Growth Curve Modeling (GCM) to estimate how months of joblessness, part-time status, and occupational mismatch during the first four years in Canada relate to immigrant men’s and women’s earnings trajectories over the following 10 years. Part-time employment, we find, is negatively associated with long-term earnings trajectories for both male and female immigrants, and male immigrants who are occupationally mismatched in the medium term also face a long-term wage penalty. Months of joblessness early on, however, is associated with relatively less wage disadvantage in later years. Since immigrants’ early difficulties are associated with long-term economic scarring, it is imperative to introduce early interventions to promote rapid assimilation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it