Clinical Ethics Fellowship Programs in the U.S. and Canada: A Descriptive Study of Program Characteristics and Practices
Bibliographic record
Abstract
To address the current lack of knowledge about clinical ethics fellowship programs (CEFPs), we surveyed all 36 programs in the U.S. and Canada. The number of CEFPs has grown exponentially over the last 40 years and far exceeds previous estimates. Commonalities among CEFPs include: 88.8% require an advanced degree or rarely accept applicants without one; 91.7% of programs do not restrict applicants to a specific background such as medicine or philosophy; and 88.9% of programs compensate fellows. CEFPs vary widely on numbers of fellows trained in the last 3 years (1-111), numbers of consultations performed by each fellow (0-450), and salaries paid ($0-$95,000). Less than half of programs meet CEFP standards established by ABPD. Nonpaying programs and larger programs tend to have lower admission standards and lower expectations for fellows. We hope these data will help inform CEFP standards that promote quality and consistency without stifling desirable diversity and innovation.
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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 | 0.063 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.024 |
| 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; 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".