Perceptions of readiness for independent practice among graduating orthopedic surgery residents in Ontario in the last 30 years
Bibliographic record
Abstract
BACKGROUND: There is increasing concern regarding the lack of physicians and underresourcing of the medical system in Canada. The training of orthopedic surgeons has emerged as an area of particular concern. The purpose of this study was to gain insight into the outcomes of graduates of orthopedic surgery residency programs in Ontario in the last 30 years. METHODS: We invited graduates of orthopedic surgery residency programs in Ontario from 1992 to 2020 to participate in our survey regarding their practice patterns and career choices. Participants were asked whether they believed their residency had prepared them for independent practice and were asked about their practice patterns after graduation, including whether they completed fellowships. RESULTS: = 253). A total of 62.8% of participants reported feeling ready to enter independent practice, which was less than the 80% expected threshold. This proportion varied by program and, overall, those who had graduated more recently reported feeling less ready. Nearly all participants had completed at least 1 fellowship, with most trainees having completed 2 fellowships. Earlier graduates were less likely to complete 2 or more fellowships. Completing a fellowship did not help with comfort in practice nor with earlier employment. Most respondents reported that their current surgical skills were primarily influenced by fellowship training, regardless of comfort level in entering practice directly out of residency. CONCLUSION: A substantial proportion of orthopedic graduates reported not feeling comfortable entering practice directly out of residency, with only 62.8% of participants reporting feeling ready for independent practice after graduation. Furtermore, graduates are incurring a significant opportunity cost completing 1 or often 2 fellowships. These findings necessitate an appraisal of our goals in residency education.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".