Bibliographic record
Abstract
Abstract: Professionalism is a core aspect of the practice of psychiatry and of medicine at large. The Royal College of Physicians and Surgeons of Canada (RCPSC) formally recognizes the importance of evaluating and teaching this competence in residency. Professionalism can be defined, measured and taught. To cultivate professional values throughout training, residency training programs need to reassess and to restructure their current curriculum. Résumé: Le professionnalisme et la formation de résidence Le professionnalisme est un aspect capital de la pratique de la psychiatrie et de la médecine en général. Le Collège royal des médecins et chirurgiens du Canada (CRMCC) reconnaît officiellement l’importance de l’évaluation et de l’enseignement de cette compétence en résidence. Le professionnalisme se définit, se mesure et s’enseigne. Pour inculquer des valeurs professionnelles en formation, les programmes d’études actuels des programmes de résidence doivent être réévalués et restructurés. Key Words: professionalism, residency, training, medical education Over the last few years, the medical world has witnessed great advances in science and technology, as well as many changes in the societal, economic and, alas, in the political scene. The current health care system is a challenging one, with increased demand for services, limited availability of resources and concerns over costeffectiveness. In such a changing context, the role and training of physicians need reviewing. In that spirit and with the impending arrival of the new millennium, the
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".