Divides of identity in medicine and surgery: A review of duty-hour policy preference
Bibliographic record
Abstract
Surgery and Medicine are broadly considered as the two fundamental paths that a physician's career can follow. But their convergence under the singular umbrella of doctoring is relatively recent in the context of medical history. Their co-existence within the structure of medical education and the healthcare system suggest that they bear great similarity to each other, when in reality several differences are intuitively recognizable between them. Here, we discuss recent evidence suggesting a discrepancy between these two streams in the work-hour policy preference of trainees. We argue that these differences betray a more radical divide between them, and one which illuminates an essential difference in the self-identification of surgical and non-surgical medical trainees. Additionally, these findings support a novel claim about the importance of uninterrupted relationships on the formation of professional identity among healthcare professionals. We suggest that the principal separation of surgical and non-surgical practice is significant enough to reconsider their dogmatic unification as well as warrant the adoption of unique rules and policies to govern each stream.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".