Bibliographic record
Abstract
ABSTRACT High‐skilled labour migration figures prominently in global policy narratives. Increasingly, countries in the global north have introduced policies to attract and facilitate the entry of skilled migrants. More recently, the high‐skilled migrant is cast as an ‘agent of development’ within policy discourse and practice. This paper challenges this rhetoric by interrogating the ways in which the North American Free Trade Agreement (NAFTA) is implicated in skilled worker mobility. Specifically, it focuses on the empirical case of the nascent continental nursing labour market to highlight the linkages between trade, migration, and development. Two specific interrelated aspects are investigated. First, the ways in which the NAFTA appeared to promote a set of linkages between nursing labour markets of Canada, US, and Mexico through its mobility provisions. Second and relatedly, the paper explores how the new continental nursing market, engendered by the NAFTA, has created a space for third party actors, most notably nursing recruiters, to facilitate cross‐border mobility of nurses. The paper emphasises the importance of considering the diverse contexts that are implicated in the production, mobility, and governance of specific skills. This consideration troubles dominate policy narratives of skilled migration as being either a boon or detriment to development goals. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".