Effect of the COVID-19 Pandemic on the Orthopaedic Surgery Residency Application Process: What Can We Learn?
Bibliographic record
Abstract
INTRODUCTION: The goal of this study was to assess the influence of the coronavirus disease 2019 pandemic on the orthopaedic surgery residency application process in the 2020 to 2021 application cycle. METHODS: A survey was administered to the program directors of 152 Accreditation Council for Graduate Medical Education-accredited orthopaedic surgery residency programs. The following questions were assessed: virtual rotations, open houses/meet and greet events, social media, the selection criteria of applicants, the number of applications received by programs, and the number of interviews offered by programs. RESULTS: Seventy-eight (51%) orthopaedic residency programs responded to the survey. Of those, 25 (32%) offered a virtual away rotation, and 57 (75%) held virtual open houses or meet and greet events. Thirteen of these programs (52%) reported virtual rotations as either "extremely important" or "very important." A 355% increase was observed in social media utilization by residency programs between the 2019 to 2020 and 2020 to 2021 application cycles, with more programs finding social media to be "extremely helpful" or "very helpful" for recruiting applicants in 2020 to 2021 compared with the previous year (39% versus 10%, P < 0.001). CONCLUSION: Although many of the changes seen in the 2020 to 2021 application cycle were implemented by necessity, some of these changes were beneficial and may continue to be used in future application cycles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".