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Record W3123707775

Empirical Impact Evaluation of the WHO Global Code of Practice on the International Recruitment of Health Personnel in Australia, Canada, UK and USA

2013· article· en· W3123707775 on OpenAlex
Jenny Edge, Steven J. Hoffman

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

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2013
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of OttawaMcMaster University
Fundersnot available
KeywordsCode of practiceWork (physics)Political scienceGlobal healthEmpirical examinationCode (set theory)Empirical researchEconomic growthBusinessPublic relationsHealth careEngineeringEconomicsActuarial scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Background: The active recruitment of health workers from developing countries to developed countries has become a major threat to global health. In an effort to manage this migration, the 63rd World Health Assembly adopted the World Health Organization (WHO) Global Code of Practice on the International Recruitment of Health Personnel in May 2010. While the Code has been lauded as the first globally-applicable regulatory framework for health worker recruitment, its impact has yet to be evaluated. We offer the first empirical evaluation of the Code’s impact on national and sub-national actors in Australia, Canada, United Kingdom and United States of America, which are the English-speaking developed countries with the greatest number of migrant health workers. Methods: 42 key informants from across government, civil society and private sectors were surveyed to measure their awareness of the Code, knowledge of specific changes resulting from it, overall opinion on the effectiveness of non-binding codes, and suggestions to improve this Code’s implementation. Results: 60% of respondents believed their colleagues were not aware of the Code, and 93% reported that no specific changes had been observed in their work as a result of the Code. 86% reported that the Code has not had any meaningful impact on policies, practices or regulations in their countries. Conclusions: This suggests a gap between awareness of the Code among stakeholders at global forums and the awareness and behaviour of national and sub-national actors. Advocacy and technical guidance for implementing the Code are needed to improve its impact on national decision-makers.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.227
GPT teacher head0.467
Teacher spread0.240 · 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