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Record W3013158179 · doi:10.1080/1369183x.2020.1731988

Intermediaries and transnational regimes of skill: nursing skills and competencies in the context of international migration

2020· article· en· W3013158179 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

VenueJournal of Ethnic and Migration Studies · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsIntermediaryCredentialContext (archaeology)BusinessPublic relationsPolitical scienceMarketingLaw

Abstract

fetched live from OpenAlex

Market-based migrant intermediaries play an important role in skilled migration. Skilled workers, especially in regulated professions such as nursing, face increasingly complex testing and credential assessment systems. ‘Regimes of skill’ control and filter membership to these professions by reproducing already existing power imbalances in the global regulation of skilled labour. This paper examines these processes in the case of Indian trained nurses who use educational brokers to enrol in Canadian post-graduate programmes with the intention of practising in the Canadian health care system. The study elaborates on the ‘regime of skill’ in nursing, revealing its maintenance through interactional and transnational connections between intermediaries, educators and regulators in terms of codifying and translating skills and competencies between jurisdictions with different cultural and professional histories and norms of nursing. Findings reveal that intermediaries operate transnationally in a symbiotic manner with more powerful actors in order to exploit regimes of skill and expand their market share.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.222

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.083
GPT teacher head0.449
Teacher spread0.367 · 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