The Education and Training of Future Physicians
Bibliographic record
Abstract
A PHYSICIAN MUST BE ABLE TO DIAGNOSE AND TREAT patients. The clinical skills required to be successful include gathering data, differentiating important from unimportant facts, making decisions about further investigations and treatments, implementing therapy, and providing follow-up, education, and counseling. These skills cannot be learned through reading or in classrooms alone; practical experience is required. The present method of exposing physicians-intraining to practical experience involves a hierarchical team approach with graded levels of responsibility whereby the decisions of the most junior members of the team are reviewed by physicians with more experience and seniority. These practical experiences impart content knowledge and also allow trainees to become comfortable with decision making and to learn the consequences of these decisions. Although there may be better ways to train future physicians, this apprenticeship method seems to work, as evidenced by the relatively low failure rate in medical schools and training programs. Part of the apprenticeship experience also includes having members at higher levels of the hierarchy evaluate those at lower levels. As such, the supervising individuals are both coaches (instructing and assisting trainees in improving their clinical skills) and judges (responsible for performance assessment of the same trainees). In this Commentary we discuss some of the problems created by this dual role and offer potential solutions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".