The Wages of Skilled Temporary Migrants: Effects of Visa Pathways and Job Portability
Bibliographic record
Abstract
Abstract We examine the earnings of highly‐skilled foreign, temporary workers and how changes in visa system affect their earnings. We use the National Science Foundation's 2003 National Survey of College Graduates and find that foreign students and temporary workers earn less than natives and permanent immigrant workers on average. Changes in visa status increase earnings, but initial visa status conditions later earnings growth along visa pathways. This implies that migrant workers ability to achieve steady, rather than discontinuous, earnings growth requires policies that make their visa portable, that it permits them to readily change employers. An admission system that favours fully‐portable permanent visas may improve worker productivity. The findings also indicate that the selectivity of foreign S&E students is not as great as that of new workers admitted from abroad; another argument against ‘stapling’ permanent visa status to foreign graduate degrees. Policy Implications Visa requirements do not ensure that temporary students and workers earn the same as similar natives during their initial period of stay. Over time this may depress occupational earnings. There is a need to reform and enforce visa regulations. Visa portability that permits ready changes in employment should better migrant earnings. Permanent admission may be preferred. Temporary foreign students experience slow earnings growth, while temporary workers hired from abroad outperform foreign graduates. The assumption that foreign graduates are the best qualified appears incorrect and facilitating (“stapling”) a green card to their diploma a poor idea.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".