The Role of Resident-Run Clinics for Aesthetic Surgery Training in the Context of Competency-based Plastic Surgery Education
Bibliographic record
Abstract
Resident-run clinics (RRCs) have been suggested as a clinical teaching tool to improve resident exposure in aesthetic plastic surgery education. In exchange for reduced cost aesthetic services, RRCs offer trainees the opportunity to assess, plan, execute, and follow surgical procedures in an independent yet supervised manner. With the transition into a competency-based medical education model involving a switch away from a time-based into a milestones-based model, the role of RRCs, within the context of the evolving plastic surgery curriculum has yet to be determined. To that end, the present study summarizes current models of aesthetic surgery training and assesses RRCs as an adjunct to aesthetics education within the framework of competency-based medical education. Explored themes include advantages and issues of RRCs including surgical autonomy, feasibility, exposure, learners' perception, ethics, and quality improvement. In addition, attention is focused on their role in cognitive competency acquisition and exposure to non-surgical techniques. RRCs are considered an effective educational model that provides an autonomous learning platform with reasonable patient satisfaction and safety profiles.
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 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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".