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Record W4283659272 · doi:10.36834/cmej.73770

Medical Council of Canada Qualifying Examinations and performance in future practice

2022· article· en· W4283659272 on OpenAlexaffvenueabout
Elizabeth Wenghofer, John R. Boulet

Bibliographic record

VenueCanadian Medical Education Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsNOSM UniversityLaurentian University
Fundersnot available
KeywordsBlueprintAccountabilityPatient careValuation (finance)Argument (complex analysis)Medical educationMedicinePsychologyNursingPolitical scienceAccountingEngineeringBusiness

Abstract

fetched live from OpenAlex

The purpose of medical licensing examinations is to protect the public from practitioners who do not have adequate knowledge, skills, and abilities to provide acceptable patient care, and therefore evaluating the validity of these examinations is a matter of accountability. Our objective was to discuss the Medical Council of Canada's Qualifying Examinations (MCCQEs) Part I (QE1) and Part II (QE2) in terms of how well they reflect future performance in practice. We examined the supposition that satisfactory performance on the MCCQEs are important determinants of practice performance and, ultimately, patient outcomes. We examined the literature before the implementation of the QE2 (pre-1992), post QE2 but prior to the implementation of the new Blueprint (1992-2018), and post Blueprint (2018-present). The literature suggests that MCCQE performance is predictive of future physician behaviours, that the relationship between examination performance and outcomes did not attenuate with practice experience, and that associations between examination performance and outcomes made sense clinically. While the evidence suggests the MCC qualifying examinations measure the intended constructs and are predictive of future performance, the validity argument is never complete. As new competency requirements emerge, we will need to develop valid and reliable mechanisms for determining practice readiness in these areas.

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)0.005
metaresearch head score (Gemma)0.057
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.057
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0200.000

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 head0.018
GPT teacher head0.309
Teacher spread0.291 · 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 designNot applicable
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

Citations10
Published2022
Admission routes3
Has abstractyes

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