Relational and embodied knowing: Nursing ethics within the interprofessional team
Bibliographic record
Abstract
In this article we attempt to situate nursing within the interprofessional care team with respect to processes of ethical practice and ethical decision making. After briefly reviewing the concept of interprofessionalism, the idea of a nursing ethic as 'unique' within the context of an interprofessional team will be explored. We suggest that nursing's distinct perspective on the moral matters of health care stem not from any privileged vantage point but rather from knowledge developed through the daily activities of nursing practice. Because of their position vis-à-vis patients and families in everyday clinical care, nurses cultivate ethical knowledge of at least two forms: (1) relational knowledge; and (2) embodied knowledge. Through the integration of these forms of knowledge, nurses develop a unique moral perspective and can make a meaningful contribution to the realm of ethics in interprofessional care.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.059 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".