Bibliographic record
Abstract
A patient's experience unfolds through a nurse's personal conversation with herself. Conveyed through three voices, the nurse's dialogue highlights her many internal struggles; those with her conscience on what she understands to be best practice, those important to her as a person, those of an ethical nature that profoundly affect one's search for meaning, and those in the personal-professional realm driven in part by institutional culture. These multivoiced knowledges are confronted in ways that foreground language and understanding as performative acts. At the same time, another journey is co-constructed with the reader, one that weaves in-between the symbolic and the real, engaging the imaginary in (inter)play. The nurse's response to the inner conversation with her 'self/selves' problematizes practice, illuminates the patient's perspective while highlighting the nurse's sense of her marginal position. Insight into reified and hegemonic assumptions, strategies of how control is maintained through organizational surveillance, trust and moral agency help to foreground personal expectations as the nurse begins to grapple with her own feelings of betrayal. Tackling these insights offers opportunities to rethink oppressive practices in the provision of care. It also enables an alternative appreciation of the everyday dilemmas confronting nurses and offers new meaning to practice.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".