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Record W2512839874 · doi:10.1097/acm.0000000000001356

The Characteristics of International Medical Graduates Who Have Been Disciplined by Professional Regulatory Colleges in Canada: A Retrospective Cohort Study

2016· article· en· W2512839874 on OpenAlexaffabout
Asim Alam, John Matelski, Hanna R. Goldberg, Jessica J. Liu, Jason Klemensberg, Chaim M. Bell

Bibliographic record

VenueAcademic Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMount Sinai HospitalUniversity Health NetworkUniversity of TorontoToronto General HospitalHelix Biopharma (Canada)Sunnybrook Health Science CentreMinistry of Health and Long Term Care
Fundersnot available
KeywordsMedicineMisconductConfidence intervalRelative riskPopulationFamily medicineDisciplineDemographyInternal medicineEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

PURPOSE: This study evaluated the proportion and characteristics of international medical graduates (IMGs) who have been disciplined by professional regulatory colleges in Canada in comparison with disciplined North American medical graduates (NAMGs). METHOD: The authors compiled a database of the nature of professional misconduct and penalties incurred by disciplined physicians from January 2000 to May 2015 using public records. They compared discipline data for IMGs versus those for NAMGs, and calculated risk ratios (RRs) and 95% confidence intervals (CIs) for select outcomes. RESULTS: There were 794 physicians disciplined; 922 disciplinary cases during the 15-year study period. IMGs composed an average of 23.4% (standard deviation = 1.1%) of the total physician population and represented one-third of disciplined physicians and discipline cases. The overall disciplinary rate for all Canadian physicians was 8.52 cases per 10,000 physician years (95% CI [7.77, 9.31]). This rate per group was higher for IMGs than for NAMGs (12.91 [95% CI (11.50, 14.43)] vs. 8.16 [95% CI (7.53, 8.82)] cases per 10,000 physician years, P < .01, and RR 1.58 (95% CI [1.38, 1.82]). IMGs were disciplined at significantly higher rates than NAMGs if they were trained in South Africa (RR 1.73 [95% CI (1.14, 2.51), P < .01), Egypt (RR 3.59 [95% CI (2.18, 5.52)], P < .01), or India (RR 1.66 [95% CI (1.01, 2.55)], P = .03). CONCLUSIONS: IMGs are disciplined at a higher rate than NAMGs. Future initiatives should be focused to delineate the exact cause of this observation.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.399
Teacher spread0.377 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2016
Admission routes2
Has abstractyes

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