Critical care nurses' efforts to pass along knowledge: a moral endeavour
Bibliographic record
Abstract
The purpose of this study was to explore and describe the work of critical care nurses to pass along knowledge of patients to other members of the health care team. Of particular interest were the following questions: which aspects of their understanding of patients do critical care nurses pass along to other health care team members; how is knowledge passed along; and for what purposes or to what ends is knowledge passed along? Data collection for this descriptive, interpretive study occurred in two intensive care units in a tertiary care hospital in Canada. Ten registered nurses, two males and eight females, volunteered to take part in the study. Participants were observed as they provided other health care providers with knowledge of the patients in their care and interviewed regarding this aspect of their work. Interpretation of the data involved multiple readings of the generated text, and a constant back and forth between parts of the text and the whole text. One theme, filling out the picture, was identified from the data. In order to fill out the picture, nurses passed along knowledge of the patient's current status, knowledge of changes in patient responses over time, knowledge the nurses believed others cared about, knowledge of interventions that worked, and knowledge of the patient as a person and member of a family. Knowledge was conveyed in different ways: as threads of data, by linking together information from the patient's body systems, through thinking out loud, by pointing, and by building a case. It was clear that the work of critical care nurses to pass along to others knowledge of the patients in their care was a moral endeavour, as evidenced by nurses' persistent and directed efforts, arising from their sense of obligation to the patient, to achieve the particular end of the well-being of patients and family members. Proximity to patients and to other health care team members was essential for this moral work.
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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 | 0.046 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.074 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.011 |
| 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".