Mexico’s brain drain to continue unabated
Bibliographic record
Abstract
Subject Mexico's brain drain. Significance Recent studies suggest increasing numbers of skilled professionals are emigrating from Mexico. A report by the University of Zacatecas (UAZ) published in March shows more than 1.4 million Mexicans with postgraduate degrees left the country between 1990 and 2015 due to a lack of professional development opportunities. According the National Council for Science and Technology (CONACYT), the government agency responsible for policy in this area, 46% of skilled emigrants live in Europe, 30% in the United States, 12% in Latin America and 7% in Canada. Impacts Emigration of skilled workers will be a fiscal burden as it annuls the benefits of investing in human resources. Policies to attract foreign talent could mitigate the problem, but there is no evidence that this is being considered. A contentious election outcome could trigger instability, further fuelling the outward flow of highly skilled Mexicans.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.048 | 0.006 |
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; both teacher heads agree on what is shown here.
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".