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Record W2134667200 · doi:10.12927/hcpap.2010.21795

Internationally Educated Health Professionals: Workforce Integration and Retention

2010· article· en· W2134667200 on OpenAlexaffvenueabout
Andrea Baumann, Jennifer Blythe, Dana Ross

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2010
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsWorkforceEconomic shortageHealth professionalsBusinessHealth carePublic relationsFace (sociological concept)Health professionsCareer PathwaysWorkforce planningNursingMedical educationMedicinePolitical scienceEconomic growthSociologyEconomicsGovernment (linguistics)

Abstract

fetched live from OpenAlex

It is essential that internationally educated healthcare professionals (IEHPs) residing in Canada re-enter and remain in their profession. To make the most of this important supply of healthcare professionals, it is vital to understand who IEHPs are, the challenges they face and how to facilitate their entry and integration into the workforce. In this article, after a summary of what is known of IEHPs who migrate to Canada, common problems of entry and integration into the workforce are discussed. Profession-specific challenges are considered, including how roles in certain professions vary globally and the importance of cultural and communication competencies. Resources to assist physicians and nurses are described and compared with those available for other professions. Finally, future possibilities and strategies for workforce integration are considered. Although the focus in this paper is on one province, the issues and strategies discussed are relevant to other provincial and international jurisdictions that are struggling with shortages and trying to capitalize on potential sources of workforce supply.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.299
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.077
GPT teacher head0.446
Teacher spread0.368 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations20
Published2010
Admission routes3
Has abstractyes

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Same venueA Nudge Too Far? A Nudge at All? On Paying People to Be HealthySame topicGlobal Health Workforce IssuesFrench-language works237,207