Variability in the Duration of Designated Pediatric Orthopaedic Rotations Among US Residency Programs
Bibliographic record
Abstract
OBJECTIVE: Our goal was to assess the variability in the assigned duration of pediatric orthopaedic rotation among US allopathic orthopaedic residency programs to see how pediatrics is incorporated into surgical education. METHODS: Using publicly available information for US allopathic orthopaedic residency programs in 2019, we retrospectively collected data on the assigned duration of pediatric orthopaedic rotation and variables such as number and sex of residents, number of orthopaedic faculty, university- versus community-based programs, outsourcing residents to unaffiliated hospital for pediatric exposure, specialty of program leadership, and presence of pediatric orthopaedic fellowship in the home program. RESULTS: One hundred thirty-eight of the 146 (95%) eligible allopathic orthopaedic residency programs provided sufficient information. The average time assigned to a pediatric rotation during residency was 6 months (range: 2 to 11 months). Overall, 43/146 (29%) programs outsourced their pediatric training to another institution. A correlation was noted between the length of pediatric rotation and percentage of pediatric orthopaedic faculty (P = 0.0007, r = 0.3). CONCLUSIONS: The impact of the variability in the duration of duration of pediatric orthopaedic rotation on the clinical knowledge and skills acquired by the resident during training needs further study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".