Growth in High-Skilled Mexican Migration Northward: American and Canadian Destinations
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
As migration of university-educated Mexicans to both the United States and Canada has begun to increase, the greater opportunities Canada’s expanding points-based selection system offers for the highly skilled to become permanent residents highlights a question: which factors may induce high-skilled Mexicans to prefer Canadian destinations versus American? Using traditional migration theories to frame interviews with a volunteer sample of 40 young university-educated Mexicans, this study confirms that reasons of proximity, climate, and culture often favor American destinations, while reasons of social acceptance, social welfare, and personal security favor Canadian. Importantly, urban-specific preferences matter. Those factors favoring U.S. destinations in general lead many to prefer southern-tier U.S. cities traditional for less-skilled Mexican migration. Those considering northern U.S. cities often prefer a Canadian choice. Canadian competitiveness in the northern urban market suggests that increased awareness of Canadian immigration opportunities could significantly boost skilled Mexican migration to Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 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