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Record W2037228908 · doi:10.1155/2015/191470

Increasing Trends in Orthopedic Fellowships Are Not due to Inadequate Residency Training

2015· article· en· W2037228908 on OpenAlexaffabout
Khaled A. Almansoori, Michael Clark

Bibliographic record

VenueEducation Research International · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsCurriculumAlgorithmMedical educationArtificial intelligenceComputer scienceMachine learningMedicinePsychology

Abstract

fetched live from OpenAlex

Orthopedic residents have one of the highest fellowship participation rates among medical specialities and there are growing concerns that inadequate residency training may be contributing to this trend. Therefore, a mixed-exploratory research survey was distributed to all 148 graduating Canadian orthopedic residents to investigate their perceptions and attitudes for pursuing fellowships. A response rate of 33% (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>49</mml:mn></mml:math>) was obtained with the majority of residents undertaking one (27%) or two (60%) fellowships. Surgical-skill development was reported as the most common motivating factor, followed by employment and marketability; malpractice protection and financial reasons were the least relevant. The overwhelming majority of residents (94%,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>46</mml:mn></mml:math>) felt adequately prepared by their residency training for independent general practice, and 84% (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>41</mml:mn></mml:math>) of respondents did not feel that current fellowship trends were due to poor residency training. Three common themes were expressed in their comments: the growing perceived expectation by healthcare professionals and employers to be fellowship-certified, the integration of fellowship training into the surgical education hierarchy, and the failure of residency training curriculums to accommodate for this trend. In conclusion, Canadian orthopedic residents are confident of their residency training and are increasingly pursuing fellowships to primarily develop their surgical skills and expertise.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.008
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.362
GPT teacher head0.498
Teacher spread0.137 · 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 designQualitative
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

Citations16
Published2015
Admission routes2
Has abstractyes

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