Bibliographic record
Abstract
Clinical ethics, as instituted in committees, aims to solve ethical problems by means of interdisciplinary deliberation. Elucidation and deliberation are used a s pragmatic means whose finality is decision-making. This being so, it may be wondered if clinical ethics has not been pruned of its more global critical potential. Narrative approaches open some ways of thinking of this critical function, but they seem to us to be nevertheless still insufficient for the task. We propose to explore the heuristic and practical fertility of the concepts of discursiveness--more inclusive than narrativity--, and co-authority--that we will have to situate and relate to notions of power, expertise and normativity--, in order to give fresh thought to the role and functions of a clinical ethics committee in a health care institution, and consequently the possible contribution of clinical ethics both as deliberation process and critical reflection of practices. To achieve this result, we propose the following approach. First of all, we will identify the limits of current narrative proposals. Secondly, we will present the concept of discursiveness based on work that follows on from the ethics of discussion. Thirdly, we will expose our definition of the concept of co-authority in a discursive space which includes both the actors of the clinical situation and the actors of the deliberation. Fourthly and finally, we will draw the consequences for a critical theory of the role and functions of a clinical ethics committee.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.073 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| 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".