Taking a Chance or Playing It Safe
Bibliographic record
Abstract
In Brief Objectives: The purpose of this study was to explore how risk is perceived and experienced by the surgeon and how risk is actively managed in individual practice. Background: Risk in surgery has been examined from system-wide and personality perspectives. Although these are important, little is known about the perspective of the individual surgeon. Methods: A constructivist grounded theory study was conducted to explore surgeons' perspectives on risk in the context of their personal “Comfort Zones.” Semistructured, 60-minute interviews were conducted with 18 surgeons who were purposively sampled for sex and subspecialty with a snowballing strategy applied to sample for differences in reputation (conservative vs aggressive). Data were collected and analyzed in an iterative manner until thematic saturation was reached. Results: Surgeons described cases that were inside or outside of their personal comfort zones. When considering cases at the boundary of their comfort zones, participants described a variety of factors that could make them feel more or less comfortable. Specific strategies used to modulate this border were also described. Two perspectives on risk taking became apparent: the procedure-centric perspective described how surgeons viewed their colleagues whereas the surgeon-centric perspective described how surgeons viewed themselves. Conclusions: A framework for understanding surgeon's unique assessment of risk was elaborated. Increased awareness of the factors and strategies identified in this study can foster critical self-reflection by surgeons of their own risk assessments and those of their colleagues, and provide avenues for more explicit educational strategies for surgical training. This qualitative study explored the contextual and personal considerations of an individual surgeon's risk assessments. Factors that influence risk assessment and strategies used by surgeons to manage risk were identified. When surgeons compared themselves with colleagues, contrasting perspectives on risk taking became apparent, which has implications for surgical culture and 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.062 | 0.018 |
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".