A hermeneutical rapprochement framework for clinical ethics practice
Bibliographic record
Abstract
BACKGROUND: A growing number of frameworks for the practice of clinical ethics are described in the literature. Among these, hermeneutical frameworks have helped highlight the interpretive and contextual nature of clinical ethics practice. OBJECTIVES: The aim of this article is to further advance this body of work by drawing on the ideas of Charles Taylor, a leading hermeneutical philosopher. DESIGN/FINDINGS: A Hermeneutical Rapprochement Framework is presented for clinical ethics practice, based on Taylor's hermeneutical "retrieval" and "rapprochement." This builds on existing hermeneutical approaches for the practice of clinical ethics by articulating a framework with interpretive and reconciliatory scope that extends beyond the presenting "local" context. A Hermeneutical Rapprochement Framework considers broader socio-historical horizons and imaginaries grounded on Taylor's expansive work in epistemological, ontological, political, and moral philosophy. DISCUSSION: The framework is discussed in terms of how it can be operationalized for clinical practice as well as normative development. Implications for the educational preparation of clinical ethicists are also discussed. Although this work is directly relevant for clinical ethicists, it can also help inform the ethical practice of all clinicians.
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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 | 0.091 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.014 | 0.132 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".