The Role of Foreign Credentials and Ethnic Ties in Immigrants’ Economic Performance
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
The literature has identified foreign credential devaluations and the shifting origins of immigrants to non-European sources as two factors that explain why some immigrants earn more than others. This study uses data from the Ethnic Diversity Survey to see how foreign credentials affect immigrants’ earnings, and whether immigrants with disadvantaged foreign credentials may be able to use ethnic social capital to mitigate the negative effect. Substantial gross earnings disparities exist among immigrant men and women of different origins, but much difference is due to human capital variations and duration of work. The study produces three major findings. First, foreign credentials benefit majority member immigrants but penalize visible minority immigrants. Second, immigrant men and women who maintain weak ethnic ties earn more than their counterparts with strong ties, suggesting that the enabling capacity of social capital for immigrants has been overstated. Third, there is no evidence of ethnic social capital being able to mitigate the negative effect of a credential deficit.
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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 | 0.002 | 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 | 0.001 | 0.002 |
| 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 it