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Record W2160133961 · doi:10.1302/0301-620x.91b12.22542

Competencies for a Canadian orthopaedic surgery core curriculum

2009· article· en· W2160133961 on OpenAlexaffabout
Veronica Wadey, Parvati Dev, Richard Buckley, Decker F. Walker, Douglas Hedden

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2009
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of AlbertaFoothills Medical CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsOrthopedic surgeryCurriculumMedicineCore competencyMedical educationCompetence (human resources)Core curriculumScale (ratio)Physical therapyPsychologySurgeryPedagogy

Abstract

fetched live from OpenAlex

We have developed a list of 281 competencies deemed to be of importance in the training of orthopaedic surgeons. A stratified, randomised selection of non-university orthopaedic surgeons rated each individual item on a scale 1 to 4 of increasing importance. Summary statistics across all respondents were given. The mean scores and sds were computed. Secondary analyses were computed in general orthopaedics, paediatrics, trauma and adult reconstruction. Of the 156 orthopaedic surgeons approached 131 (84%) responded to the questionnaire. They rated 240 of the 281 items greater than 3.0 suggesting that competence in these was necessary by completion of training. Complex procedures were rated to be less important. The structure, delivery and implementation of the curriculum needs further study. Learning activities are 'driven' by the evaluation of competencies and thus competency-based learning may soon be in the forefront of training programmes.

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)0.001
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 score0.487
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.238
Teacher spread0.219 · 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

Citations27
Published2009
Admission routes2
Has abstractyes

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