Lessons From Rocket Science: Reframing the Concept of the Physician Health Advocate
Bibliographic record
Abstract
Health advocacy is a prominent component of health professionals' training internationally and is frequently discussed in the medical education literature. Despite this, it continues to be a problematic and challenging topic for medical educators, health professionals, and trainees alike. Borrowing from the field of systems engineering, the authors suggest a need to reconceptualize health advocacy using a systems mind-set rather than a physician-centric perspective. Conceptualizing health advocacy as a systemic, collective effort requires educators, practitioners, and trainees to challenge the assumption that the role of a competent physician health advocate can be fully defined without regard to the larger system or collective within which physicians function. Further, this implies a substantially more dynamic understanding of physicians' and other participants' parts in the collective activity.Of course, this new way of conceptualizing physicians' practices is not limited to health advocacy. The current education paradigm trains physicians for individual competency but expects them to practice collectively. Defining physician competen cies, or the competencies of any health care provider, in isolation from the particular system of which that individual is an integral part implicitly places that health care provider as the central focus of that system. Thus, academic medicine needs to move its educational and research efforts forward in a manner that recognizes that a systems engineering approach to health improvement will allow the various players to maximize their individual efforts to more effectively support the collective activity.
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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 | 0.052 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.015 | 0.120 |
| Scholarly communication | 0.024 | 0.031 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.022 | 0.040 |
| Insufficient payload (model declined to judge) | 0.005 | 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".