Bibliographic record
Abstract
To the Editor: The recent Academic Medicine article by Riesenberg and colleagues,1 designed to describe the historical development of nonphysician medical educators and develop a job description resource, was comprehensive in its scope. However, the article and one of the accompanying commentaries2 raise a significant concern that we must address as a community of medical educators. I am a clinical psychologist who has worked in medicine for over 25 years—as a clinical psychologist and therapist, as a teacher and supervisor, as a faculty developer, and as a medical educator. At no time have I considered or called myself a nonphysician medical educator (or NPME, an acronym used in the commentary).2 In fact, I strongly believe that (1) my identity is defined by who I am and by what I do—not by what I am not, (2) nonphysicians are not a homogeneous group—just as physicians are not, and (3) the notion of non implies a concept of exclusion, not inclusion, and by default does not promote interprofessional respect or collaboration. At a recent meeting of the Association for Medical Education in Europe, I asked a group of medical educators how they define themselves. Their responses ranged from physician and nurse to sociologist, anthropologist, political scientist, basic scientist, researcher, and educator. No one defined themselves as nonphysicians. Although I realize that the literature uses that term, I would think that a comprehensive review such as the one by Riesenberg and colleagues should have addressed the term's limitations and not continued to promote a homogenized view of roles and history. In addition, the authors, all respected individuals in their fields, should have specified their search terms so that we could begin to understand the discourse that is used in the literature. We should also be aware of the discourse in their article. Why, for example, might it be necessary to “replace” the physician educator? And why should we “use” nonphysician medical educators to “control costs” or view these individuals as a “cost-effective way to meet medical education needs”? In my opinion, we are all in this endeavor together. Some might suggest that I should propose an alternate term for nonphysicians. I would argue, however, that we should not lump any group of individuals (or professionals) into one category; rather, we should acknowledge the breadth and depth of the different skills we all bring to medical education and begin to appreciate heterogeneity. We should also value diverse strengths and abilities and recognize individual identities: We all are who we are, not who we are not. Yvonne Steinert, PhD Associate dean, faculty development, and director, Centre for Medical Education, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; [email protected].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".