Rethinking medical oaths using the Physician Charter and ethical virtues
Bibliographic record
Abstract
OBJECTIVE: Medical oaths express ethical values that are essential to the trust within the patient-physician relationship and medicine's commitment to society. However, the contents of oaths vary between medical schools and therefore raise questions about which ethical values should be included in a medical oath. More than a decade has passed since this variability was last analysed in North America, and since that time the Physician Charter on Medical Professionalism has gained considerable attention, raising the possibility that the Charter may be influencing medical oaths and making them more consistent. METHODS: The authors conducted a content analysis of 84 oaths available in 2015 from medical schools in the USA and Canada affiliated with the Association of American Medical Colleges, organising the content into three categories: (i) ethical values, (ii) principles and commitments in the Physician Charter, and (iii) ethical virtues. RESULTS: Only five ethical values were expressed in the majority of oaths (confidentiality, obligation to the profession, beneficence, avoiding discrimination, and honour and integrity), and respect for patient autonomy was uncommon. Only three of the Physician Charter's principles and commitments (primacy of patient welfare, social justice and confidentiality) and one virtue (honour and integrity) were reflected in the majority of oaths. CONCLUSIONS: Medical oaths in North America appear to be highly variable in content. Greater attention to resources like the Physician Charter can help improve the ethical content and consistency of oaths across different institutions, and throughout their education medical students should be encouraged to discuss and reflect on the principles and virtues they will profess when they graduate.
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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 | 0.014 | 0.092 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".