Imagining a continuing interprofessional education program (CIPE) within surgical training
Bibliographic record
Abstract
In recent years increasing attention has been paid to issues of professionalism in surgery and the content and structure of continuing professional development for surgeons; however, little attention has been paid to interprofessional education (IPE) in surgical training. Imagining the form(s) of IPE and/or continuing interprofessional education (CIPE) programs within surgical training requires serious attention to 2 fundamental issues--the discourses of professionalism in surgery and the professional culture of surgery, as shaped and expressed within the clinical setting. We explore the possibility that concepts of professionalism within surgery may be in conflict with the tenets of interprofessionalism held by other health and medical professionals. We believe that if any rapprochement is to occur between the concept of professionalism in surgical training (and within the everyday clinical culture of surgical subspecialties groups and their professional institutions) and broader discourses of interprofessionalism circulating within health care institutions, there is a pressing need to understand and deconstruct this conflict from the point of view of surgery.
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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 | 0.024 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| 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".