Credentialing the Clinical Ethics Consultant: An Academic Medical Center Affirms Professionalism and Practice
Bibliographic record
Abstract
In response to national trends calling for increasing accountability and an emerging dialogue within bioethics, we describe an effort to credential clinical ethicists at a major academic medical center.This effort is placed within the historical context of prior calls for credentialing and certification and efforts currently underway within organized bioethics to engage this issue.The specific details, and conceptual rationale, behind the NewYork-Presbyterian Hospital's graduated credentialing plan are shared as is their evolution and ratification within the context of institutional policy. While other programs will design their credentialing schema consistent with their local context and demographics, the description of one such effort is offered to be instructive to others who want to bring additional standardization to the assessment of the readiness and credentials of those who will engage in the practice of clinical ethics case consultation.
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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 | 0.019 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.013 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 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".