Ethical Care of the Critically Ill Child: a conception of a ‘thick’ bioethics
Bibliographic record
Abstract
In this article I argue for an interpretive approach to bioethics with critically ill children. I begin by highlighting the dominant Anglo-American bioethical framework that defines standards for ethical care in critically ill children and then outline a critique of this framework. Drawing predominantly on the ideas of Charles Taylor, Michael Walzer and Richard Zaner, I call for a reconception of bioethics and propose an interpretive 'thick' framework that is centred on culture and context. Finally, I illustrate this interpretive approach through a comparative study of two cases in pediatric intensive care: the narratives of Marc and Larry. These case studies reveal that ethical dilemmas in pediatric critical care can be traced to relational tensions over respect, trust and power rooted in the disparity of moral horizons among the persons involved.
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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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.096 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.001 | 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".