Bus stops, triple wins and two steps: nurse migration in and out of Asia
Bibliographic record
Abstract
Abstract The migration pathways in which nurses engage are increasingly heterogeneous. In this article, I contrast three types of nurse migration pathway from three country pairs – Vietnam to Germany ‘triple win’ bi‐lateral migration (direct migration); India to Canada two‐step study‐work (multistage) pathway; and ‘bus stop’ multinational migration from the Philippines to Singapore and onwards to other sites. Each pathway is not exclusive to the country pair selected; rather, this occupational and pathway specific analysis permits a comparison of the structures and processes involved – the different kinds of hierarchies that underpin mobility; the migration and border‐control infrastructure that channels mobility; and the differential incorporation of multi‐nationally mobile lives and their gendered/racialized implications. The migration trajectories analysed in this article reveal how multinational and multistage migrations are produced (through state and non‐state intermediaries and policy structures), and how they are productive of new subjectivities and imaginaries (shaped by what is possible and desirable).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".