Embodied knowing? The constitution of expertise as moral practice in nursing
Bibliographic record
Abstract
Prominent nursing authors, such as Patricia Benner, are influential in the increasing trend to conceptualize ethics as a contextual and embodied way of knowing, embedded in nursing expertise. It will be argued here that rather than revealing a moral truth manifest in practice, the idea of ethics as expertise constitutes nursing practice as a moral endeavour and the nurse as a practitioner who has acquired a particular moral deportment. In fact, the case will be made that the expert nurse as a moral and ethical category is the result of the elaboration of prestigious humanistic discourses in the educational and professional shaping of nurses. These discourses act on and are enacted by the individual nurse through his or her participation in specific ethical exercises that result in the constitution of the desired subjectivity. Of critical importance here is the widespread adoption in nursing pedagogy and professional literature of phenomenological perspectives on the body and nursing practice. This paper examines both the intellectual origins and contemporary implications of this trend for practicing nurses.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.089 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".