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Record W2056959926 · doi:10.2147/rmhp.s60708

“Brain drain” and “brain waste”: experiences of international medical graduates in Ontario

2014· article· en· W2056959926 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

VenueRisk Management and Healthcare Policy · 2014
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsSt. Michael's HospitalUniversity of TorontoCanadian Institutes of Health Research
Fundersnot available
KeywordsBrain drainThematic analysisSocioeconomic statusDeveloping countryMedicinePosition (finance)Descriptive statisticsBusinessMedical educationQualitative researchDemographic economicsEconomic growthEnvironmental healthPopulationSociologyEconomicsSocial scienceFinance

Abstract

fetched live from OpenAlex

BACKGROUND: "Brain drain" is a colloquial term used to describe the migration of health care workers from low-income and middle-income countries to higher-income countries. The consequences of this migration can be significant for donor countries where physician densities are already low. In addition, a significant number of migrating physicians fall victim to "brain waste" upon arrival in higher-income countries, with their skills either underutilized or not utilized at all. In order to better understand the phenomena of brain drain and brain waste, we conducted an anonymous online survey of international medical graduates (IMGs) from low-income and middle-income countries who were actively pursuing a medical residency position in Ontario, Canada. METHODS: Approximately 6,000 physicians were contacted by email and asked to fill out an online survey consisting of closed-ended and open-ended questions. The data collected were analyzed using both descriptive statistics and a thematic analysis approach. RESULTS: A total of 483 IMGs responded to our survey and 462 were eligible for participation. Many were older physicians who had spent a considerable amount of time and money trying to obtain a medical residency position. The top five reasons for respondents choosing to emigrate from their home country were: socioeconomic or political situations in their home countries; better education for children; concerns about where to raise children; quality of facilities and equipment; and opportunities for professional advancement. These same reasons were the top five reasons given for choosing to immigrate to Canada. Themes that emerged from the qualitative responses pertaining to brain waste included feelings of anger, shame, desperation, and regret. CONCLUSION: Respondents overwhelmingly held the view that there are not enough residency positions available in Ontario and that this information is not clearly communicated to incoming IMGs. Brain waste appears common among IMGs who immigrate to Canada and should be made a priority for Canadian policy-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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
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 head0.056
GPT teacher head0.431
Teacher spread0.375 · 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