Migration, Development and US Labor Markets: The Mexican-US Case
Bibliographic record
Abstract
This paper explores economic and technological changes and the evolution of labor markets in sending and receiving countries, with an emphasis on developments in a major emigration country, Mexico, and the impacts of migrants from Mexico and Latin America on the labor markets of Canada and the US. There are four major conclusions. Firstly, while immigrant workers are important in many industries, occupations, and areas, no major US industry or occupation is dependent on foreign-born or Mexican-born workers. Secondly, Mexican-born workers tend to be near the low end, often filling jobs that would be eliminated or modified by technology if wages rose. Thirdly, the short- and long-run effects of trade and investment on migration may be very different, producing a migration hump in the short-term that may increase migration flows before they decline. Finally, current demographic changes in Mexico's labor market can lead to a near-term decline in the volume of unauthorized migration to the United States even if emigration probabilities continue to rise moderately. Mexico, the US, and Canada are on the path toward closer economic integration that could soon reduce permanent or settler migration, even as temporary or sojourner migration increases for business and other purposes. The reduction in emigration pressure in Mexico may be noticeable sooner than is commonly realized for demographic and economic reasons. The policy challenge is to do no harm, to avoid policies that produce unintended negative consequences or that prolong Mexican-US unauthorized migration during the transition.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".