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Record W1621930088 · doi:10.3138/cpp.2014-037

Demographics, Debt, and Practice Intentions of Medical Residents Training in Canada

2015· article· en· W1621930088 on OpenAlexaffvenueabout
Lori J. Curtis, Umber Dube

Bibliographic record

VenueCanadian Public Policy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDemographicsDebtStudent debtHealth careMedical educationMedicineFamily medicinePsychologyPolitical scienceBusinessFinanceDemographySociology

Abstract

fetched live from OpenAlex

Many international medical graduates (IMGs) are unable to find residency positions in Canada. A growing proportion are “Canadians studying abroad” (CSAs) trying to return to Canada. We examine the characteristics and practice intentions of residents in Canada: IMGs excluding CSAs, CSAs, and Canadian medical school graduates (CMGs). CSAs and CMGs appear to be similar, but IMGs do not in key instances. IMGs are substantially less likely to state that they intend to practise where they trained or in Canada, controlling for characteristics. This adds support to previous findings indicating that regions relying on IMGs to provide health care may experience ongoing challenges.

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)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.135
GPT teacher head0.456
Teacher spread0.322 · 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; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2015
Admission routes3
Has abstractyes

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