Informed Strangers: Witnessing and Responding to Unethical Care as Student Nurses
Bibliographic record
Abstract
Nursing students occupy a unique perspective in clinical settings because they are informed, through education, about how patient care ought to happen. Given the brevity of placements and their "visiting status" in clinical sites, students are less invested in the ethos of specific sites. Subsequently, their perspectives of quality care are informed by what should happen, which might differ from that of nurses and patients. The purpose of this study was to identify predominant themes in patient care, as experienced by students, and the influence that these observations have on the development of their ethical reasoning. Using a qualitative descriptive approach in which 27 nursing student papers and three follow-up in-depth interviews were analyzed, three main themes emerged: Good employee, poor nurse; damaged care; and negotiating the gap. The analysis of the ethical situations in these papers suggests that students sometimes observe care that lacks concern for the dignity, autonomy, and safety of patients. For these student nurses, this tension led to uncertainty about patient care and their eventual profession.
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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 | 0.029 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.026 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".