FAMILY REUNIFICATION OR POINT-BASED IMMIGRATION SYSTEM? THE CASE OF THE U.S. AND MEXICO *
Bibliographic record
Abstract
While the immigration policy in the U.S. is mainly oriented to family reunification, in Australia, Canada and the U.K. it is a points-based immigration system which main objective is to attract high skilled immigrants. This paper compares both immigration policies through the transition for the U.S. and Mexico. I find that: (i) The point system increases the average years of the immigrants by 3.5 years. (ii) The Mexican immigrants suffer a 10% reduction in their effective hours of labor when they move to the U.S. (iii) Migration reduces inequality, more significantly if the immigration policy is the point system and increases output per capita differences between both countries. (iv) The offspring of the immigrants invest more in human capital than the U.S. natives. (v) The earnings ratio immigrants to the U.S. natives is lower under the quota system than under the point system but along the transition it reverses converging at the steady state.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".