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The rise of practice development with/in reformed bureaucracy: discourse, power and the government of nursing

2011· review· en· W2138115399 on OpenAlexaff
Trudy Rudge, Dave Holmes, Amélie Perron

Bibliographic record

VenueJournal of Nursing Management · 2011
Typereview
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsManagerialismPanacea (medicine)IdeologyPower (physics)SociologyNursingBureaucracyNursing researchGovernment (linguistics)Health careNursing managementPublic relationsMedicinePolitical scienceLinguisticsPoliticsLawAlternative medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.376
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2011
Admission routes1
Has abstractyes

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