“Staying in the Game”: How Procedural Variation Shapes Competence Judgments in Surgical Education
Bibliographic record
Abstract
PURPOSE: Emerging research explores the educational implications of practice and procedural variation between faculty members. The potential effect of these variations on how surgeons make competence judgments about residents has not yet been thoroughly theorized. The authors explored how thresholds of principle and preference shaped surgeons' intraoperative judgments of resident competence. METHOD: This grounded theory study included reanalysis of data on the educational role of procedural variations and additional sampling to attend to their impact on assessment. Reanalyzed data included 245 hours of observation across 101 surgical cases performed by 29 participants (17 surgeons, 12 residents), 39 semistructured interviews (33 with surgeons, 6 with residents), and 33 field interviews with residents. The new data collected to explore emerging findings related to assessment included two semistructured interviews and nine focused field interviews with residents. Data analysis used constant comparison to refine the framework and data collection process until theoretical saturation was reached. RESULTS: The core category of the study, called staying in the game, describes how surgeons make moment-to-moment judgments to allow residents to retain their role as operators. Surgeons emphasized the role of principles in making these decisions, while residents suggested that working with surgeons' preferences also played an important role in such intraoperative assessment. CONCLUSIONS: These findings suggest that surgeons' and residents' work with thresholds of principle and preference have significant implications for competence judgments. Making use of these judgments by turning to situated assessment may help account for the subjectivity in assessment fostered by faculty variations.
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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 | 0.009 | 0.048 |
| 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 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".