Complémentarité des rôles clinico-administratifs infirmiers en contexte hospitalier : une étude de cas
Bibliographic record
Abstract
INTRODUCTION AND BACKGROUND: The roles of head nurse (HN) and charge nurse (CN) in hospital care units are intended to be complementary, but still remain ambiguous. Studying the complementarity of these roles is a unique way of looking at them. OBJECTIVE: To explain in which circumstances the complementarity of HNs and CNs occurs in a hospital setting. METHODS: A single case study with the inclusion of complementary data from fifteen interviews with HNs and CNs and from documentary sources (n = 80). RESULTS: Fifteen independent or interdependent role components with potential complementarity were identified. This complementarity can be explained by way of three elements: 1) the CN's partial perspective and the HN's global perspective; 2) bidirectional communication; 3) common objectives requiring team mobilization. DISCUSSION AND CONCLUSION: Studying complementarity is an innovative approach that provides an understanding of the work of both HNs and CNs, as well as allowing us to understand how they complement each other and how one's work increases the value of the other's and vice-versa, resulting in improved quality of care.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".