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Record W4242291261 · doi:10.32920/ryerson.14662380

An assessment of the barriers regarding international medical doctors' path to licensure in Ontario and the initiatives put forth to tackle these challenges

2021· preprint· en· W4242291261 on OpenAlexaffabout
Lida Moazzam

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsAccreditationLicensureEconomic shortageHealth careFace (sociological concept)Process (computing)Order (exchange)BusinessPublic relationsCareer pathPolitical scienceMedical educationMedicineComputer scienceSociologyFinance

Abstract

fetched live from OpenAlex

Upon arrival to Canada, International Medical Doctors (IDMs) must undergo a lengthy and complex process in becoming accredited in order to be able to practice in this country, IMDs have historically contributed substantially to the Canadian healthcare system and have great potential to tackle the current physician shortages in the provinces. However, although they have significant skills and experience and can be regarded as a fairly obvious resource to address the physician shortage, their potential remains underutilized. Therefore, this major research paper will focus on the province of Ontario to examine some of the barriers IMDs face in their path to re-entering their profession and outline and assess some of the initiatives and programs put forth to tackle some of these challenges faced by IMDs in this province.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.468
Teacher spread0.412 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2021
Admission routes2
Has abstractyes

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