Challenging transitions? Assessing the occupational mobility patterns of US immigrants by gender
Bibliographic record
Abstract
Abstract This article uses the New Immigrant Survey to assess the occupational mobility of US immigrants. Estimates from OLS and Heckman selection models show the occupational mobility of immigrants follows a U‐shaped pattern: immigrants arriving in the United States see their occupational status decline before it gradually improves. However, even 9 years after coming to the United States, the occupational status of immigrants remains lower than prior to their arrival in the country. Our findings also suggest that immigrant women with higher occupational status tend to move more often to the United States than immigrant men. Conversely, immigrant women are more likely than men to experience career interruptions after migration. Finally, occupational employment growth rates (defined as the growth rate in the number of jobs for an occupation) have a positive impact on both men and women immigrants' ability to recover their occupational status, though the impact appears to be greater for immigrant women.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".