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Record W2545420779 · doi:10.1177/084456211404600307

Seeking Connectivity in Nurses' Work Environments: Advancing Nurse Empowerment Theory

2014· article· en· W2545420779 on OpenAlexaffvenueabout
Sonia Udod

Bibliographic record

VenueCanadian Journal of Nursing Research · 2014
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEmpowermentPsychologyPower (physics)Work (physics)NursingSociologyPolitical scienceManagementHumanitiesMedicineEngineering

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate how staff nurses and their managers exercise power in a hospital setting in order to better understand what fosters or constrains staff nurses' empowerment and to extend nurse empowerment theory. Power is integral to empowerment, and attention to the challenges in nurses' work environment and nurse outcomes by administrators, researchers, and policy-makers has created an imperative to advance a theoretical understanding of power in the nurse-manager relationship. A sample of 26 staff nurses on 3 units of a tertiary hospital in western Canada were observed and interviewed about how the manager affected their ability to do their work. Grounded theory methodology was used. The process of seeking connectivity was the basic social process, indicating that the manager plays a critical role in the work environment and nurses need the manager to share power with them in the provision of safe, quality 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 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)0.006
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.020
Scholarly communication0.0050.008
Open science0.0010.006
Research integrity0.0010.002
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 head0.030
GPT teacher head0.367
Teacher spread0.338 · 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
GenreEmpirical

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

Citations7
Published2014
Admission routes3
Has abstractyes

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