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Record W1983802228 · doi:10.1503/cjs.006614

Supply versus demand: a review of application trends to Canadian surgical training programs

2015· review· en· W1983802228 on OpenAlexaffvenueabout
Ryan E Austin, Kyle R. Wanzel

Bibliographic record

VenueCanadian Journal of Surgery · 2015
Typereview
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsSt Joseph's Health CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineMedical educationResidency trainingSurgical proceduresSurgery

Abstract

fetched live from OpenAlex

Despite increases in medical school enrolment, applications to surgical residency programs in Canada have been in decline over the past decade, with an increasing number of unmatched surgical residency positions. We examined the current status of surgical residency in Canada and analyzed application trends (2002–2013) for surgical training programs across Canada. Our findings suggest that most undergraduate medical schools across Canada are having difficulty fostering interest in surgical careers. We propose that a lack of adequate early exposure to the surgical specialties during undergraduate training is a critical factor. Moving forward, we must examine how the best-performing institutions and surgical programs have maintained interest in pursuing surgical careers and adapt our recruitment methods to both maintain and grow future interest. As Mary Engelbreit said, "If you don't like something, change it; if you can't change it, change the way you think about it."

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.922
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.271
GPT teacher head0.391
Teacher spread0.121 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2015
Admission routes3
Has abstractyes

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