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Record W2882999890 · doi:10.5430/jnep.v8n12p21

Nurses’ lived experience serving on unit-based councils: A literature review

2018· review· en· W2882999890 on OpenAlexvenueno aff
Alanoud Hamad, Vahe Kehyayan

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typereview
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsnot available
Fundersnot available
KeywordsUnit (ring theory)NursingPerceptionJob satisfactionWork (physics)Nursing managementPsychologyMedicineSocial psychologyEngineering

Abstract

fetched live from OpenAlex

Introduction: Shared governance (SG) is an organizational model that allows frontline nurses to have control over their daily work environment and nursing practice. Unit-based councils (UBC) are an important operational element of SG and its members are frontline nursing staff.Purpose and methods: The purpose of this paper is to review the literature on UBCs and SG, staff nurses’ perceptions, and factors that influence their adoption and successful implementation.Results: Five major themes emerged from the literature: perception of SG; leadership implications; improvement in patient care; increase in job satisfaction; and improvement in work environment.Conclusions: Nurses serving on UBCs have perspectives different from managers on the success of SG and UBCs. SG is viewed as a journey that requires continuous support from nurse leaders to address any issues that may arise during this journey.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.346
GPT teacher head0.597
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations5
Published2018
Admission routes1
Has abstractyes

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