Nursing resistance as ethical action: literature review
Bibliographic record
Abstract
BACKGROUND: Much has been written about nursing as a predominantly female profession whose members display passivity, submission, obedience and powerlessness. Alternatively, some authors have presented evidence of nurses' capacity to exercise power, revealing the possible relationship between powerlessness and ethical compromise. Thus, empowerment strategies for nurses can yield ethical action. AIM: The aim of this paper is to use analysis of the literature to demonstrate how the actions and responses of nurses to ethical concerns are examples of nurses exercising power. METHOD: Empirical studies published in the nursing literature between 1990 and 2003 have been analysed to illustrate how nurses' actions of resistance can ensure that moral values are realized in practice. Foucauldian notions of power relations and feminist ethics provide the theoretical framework. CONCLUSIONS: Nurses were found to resist in situations where they experienced moral conflicts in relation to the actions of health professionals; however, instances were cited where they did not. Consequently, strategies for nursing education and management are proposed to increase nurses' understanding of the potential acts of resistance that they could employ in situations of moral conflict or concern.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".