Immigration and Education: Setbacks and Opportunities For Earnings along the Texas–Mexico Border
Bibliographic record
Abstract
This paper examines returns to education and income determinants of residents along the Texas–Mexico border, using the 2006–2008 3-Year American Community Survey data. The returns to education are higher along the border than in the rest of Texas, especially for college educated Hispanic women, suggesting high demand for bilingual professionals. In regressions focusing on the border, controls for English ability and other income factors makes the Hispanic variable insignificant. While in regressions focusing on the rest of Texas, being Hispanic has little impact on earnings. The immigrant variable decreases earnings by 7% along the border, but is positive elsewhere in Texas, suggesting immigrants are relatively well paid for their skill level, but comparatively low skills cause low average earnings. Finally, the border region potentially loses over $900 per adult a year due to lower earnings power from relatively low education levels compared to the rest of the state. Hispanics have the lowest education attainment and compared to the earnings of non-Hispanics with higher education attainment, may miss out on over $2,200 a year.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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 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".