A necessary paradigm shift: recognizing the surgeon-advocate in academic surgery
Bibliographic record
Abstract
Health equity and the social determinants of health are increasingly prioritized in health care delivery across North America and globally, yet academic medicine remains ill equipped to support equity-focused advocacy. We argue that this stems mainly from a gap in recognizing advocacy as an academic pillar alongside research, education, and administration. Advocacy is undervalued in academic medicine, as reflected in teaching, hiring, and promotion criteria and what is published in academic journals. Health equity is essential for the health of populations, and the current structure of academic medicine should be redesigned to recognize, value, and support equity-based advocacy efforts. Advocacy can be integrated in 2 key areas: medical education and faculty roles and promotion pathways. A new academic role, the surgeon-advocate - whose work focuses on the engagement, knowledge dissemination, and administration of advocacy-based work to affect system change - is vital for a paradigm shift that accepts advocacy into the essential work of academic medicine. The concept of a surgeon-advocate is not new and is vital to our identities as physicians. However, formally embracing advocacy within academic institutions represents the paradigm shift needed to move closer to health equity goals. This analysis proposes a critical revision to academic surgery and, more broadly, academic medicine. We provide practical steps to intentionally weave advocacy and health equity into the fabric of academic medical institutions to improve how we practise and serve our patients.
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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 | 0.132 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.032 | 0.102 |
| Scholarly communication | 0.036 | 0.038 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.025 | 0.044 |
| Insufficient payload (model declined to judge) | 0.004 | 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".