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Record W2074254107 · doi:10.1007/s00268-006-0267-2

A Better Lifestyle During Surgical Clerkship May Not Increase Application Rates to General Surgery

2007· article· en· W2074254107 on OpenAlexaffabout
Samuel Minor, Jason Park, Paul Belliveau, Ross Walker

Bibliographic record

VenueWorld Journal of Surgery · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of ManitobaKingston General HospitalQueen's University
Fundersnot available
KeywordsMedicineAbdominal surgeryVascular surgeryMedical schoolSurgeryGeneral surgeryMedical educationCardiac surgery

Abstract

fetched live from OpenAlex

BACKGROUND: Lifestyle has been identified by numerous studies as the number one deterrent to pursuing a career in general surgery. This study tests the hypothesis that a better lifestyle during general surgery clerkship correlates with a higher application rate to general surgery. METHODS: Canadian Residency Matching Service data from the past 10 years were used to identify institution-specific application rates to general surgery. Through a survey of all fourth-year medical students applying to general surgery in Canada and Canadian undergraduate surgery program directors, the lifestyle of each general surgery clerkship was described and given a score. RESULTS: Multiple descriptions of the clerkship structure were obtained for every school in Canada to reduce recall bias, with an average of 4 sources per program. One school stood out as the most prolific producer of general surgery applicants, with an average of 7.9% of the total class applying to general surgery each year. This represented 80% more general surgery applicants relative to the national average (p < 0.05). Surprisingly, however, this institution also had the worst clerkship lifestyle score, having a higher call requirement, not sending their clerks home at noon post call, and placing a higher burden of responsibility on their clerks. CONCLUSIONS: This study suggests that a lifestyle-friendly surgical clerkship may not be necessary to increase recruitment into general surgery.

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)0.010
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.040
GPT teacher head0.309
Teacher spread0.270 · 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

Citations4
Published2007
Admission routes2
Has abstractyes

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