Implementing evidence‐based nursing practice: a tale of two intrapartum nursing units
Bibliographic record
Abstract
Despite concerns that the rise of evidence-based practice threatens to transform nursing practice into a performative exercise disciplined by scientific knowledge, others have found that scientific knowledge is by no means the preeminent source of knowledge within the dynamic settings of health-care. We argue that the contexts within which evidence-based innovations are implemented are as influential in the outcomes as the individual practitioners who attempt these changes. A focused ethnography was done in follow-up to an earlier trial that evaluated the effectiveness of a marketing strategy to encourage the adoption of evidence-based intrapartum nursing practice. Bourdieu's (1990, 1991) concepts of habitus, capital and social field were used in our refinement of the analysis of the ethnographic findings. Nursing leadership, interprofessional struggle with physicians, the characteristics of the community and the physical environment were prominent issues at all of the sites. Detailed descriptions of the sociohistorical context and of the experiences at two sites are presented to illustrate the complexities encountered when implementing innovations.
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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 | 0.023 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.017 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".