Bibliographic record
Abstract
In the context of nurse migration, experts view trade agreements as either vehicles for facilitating migration or as contributing to brain-drain phenomena. Using a case study design, this study explored the effects of the North American Free Trade Agreement (NAFTA) on the development of Mexican nursing. Drawing results from a general thematic analysis of 48 interviews with Mexican nurses and 410 primary and secondary sources, findings show that NAFTA changed the relationship between the State and Mexican nursing. The changed relationship improved the infrastructure capable of producing and monitoring nursing human resources in Mexico. It did not lead to the mass migration of Mexican nurses to the United States and Canada. At the same time, the economic instability provoked by the peso crisis of 1995 slowed the implementation of planned advances. Subsequent neoliberal reforms decreased nurses' security as workers by minimizing access to full-time positions with benefits, and decreased wages. This article discusses the linkages of these events and the effects on Mexican nurses and the development of the profession. The findings have implications for nursing human resources policy-making and trade in services.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".