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Record W1992238946 · doi:10.1080/10401334.2012.641484

Evaluation of Medical Career-Counseling Resources Across Canada

2012· article· en· W1992238946 on OpenAlexaffabout
June Harris, Donald W. McKay

Bibliographic record

VenueTeaching and Learning in Medicine · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGraduation (instrument)AccreditationSpecialtyMedical educationCareer counselingFamily medicineMatching (statistics)PsychologyService (business)MedicineBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: North American medical school accreditation requires career counseling. PURPOSE: The Memorial University of Newfoundland (MUN) MedCAREERS program was implemented in 2000 before published evidence of efficacy of Canadian medical school career-counseling programs existed. METHODS: Data were gathered initially through the Canadian Residency Matching Service Post-Match Survey in 2003 and subsequently through the Canadian Graduation Questionnaire from 2006 to 2008. The overall response rate was 61%. Perceived benefits and efficacy of the MUN MedCAREERS Web site and several career-counseling resources were determined along with participation rates encompassing a 6-year period. RESULTS: Most career-counseling resources were perceived as helpful, regardless of participation rate. CONCLUSIONS: Our goal was to provide information on an array of career-counseling resources so that Canadian medical schools can avail of appropriate resources and select activities to help students make informed decisions about their specialty choice. Planners of career-counseling activities may wish to consider elements that students find most helpful.

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)0.007
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.948
Threshold uncertainty score0.378

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0070.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.371
Teacher spread0.315 · 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 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

Citations9
Published2012
Admission routes2
Has abstractyes

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