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Record W3044531062 · doi:10.1111/glob.12296

Bus stops, triple wins and two steps: nurse migration in and out of Asia

2020· article· en· W3044531062 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGlobal Networks · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsMultinational corporationIntermediaryDifferential (mechanical device)State (computer science)Economic geographyIrregular migrationWork (physics)Political scienceBusinessGeographyComputer scienceEngineeringMarketing

Abstract

fetched live from OpenAlex

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).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.291
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it