The rise of practice development with/in reformed bureaucracy: discourse, power and the government of nursing
Bibliographic record
Abstract
AIM: Using a neo-Foucauldian approach, a critique of texts explicitly dealing with the definitional work for practice development (PD) was undertaken. BACKGROUND: PD has been taken up by many organizations as a way of focusing on nurses' practices to benefit patients and the organization. EVALUATION: Literature pertaining to the PD phenomenon was examined and the present study explores those texts accomplishing definitional work. The discourse corpus collected together articles in nursing journals, book chapters and textbooks. The corpus was analysed using the discourse analysis method. KEY ISSUES: PD uses and manipulates its location in a network of managerialism, evidence-based nursing, safety and quality discourses in healthcare to verify (and confirm) its definition and its position as central to progress in nursing practice. CONCLUSION: We argue that while PD is portrayed as 'emancipatory' and transforming, nurses bear the responsibility for the system and its failures in a web of intricate power relations. IMPLICATIONS FOR NURSING MANAGEMENT: The present study offers a review of the PD ideology in nursing where a critical perspective has yet to be found. Nursing managers should understand that PD is not a panacea for improving patient 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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.031 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".