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Record W2953365378 · doi:10.12927/cjnl.2019.25847

Process and Initial Outcomes of an Initiative to Engage Nurses at a Mental Health and Addictions Hospital

2019· article· en· W2953365378 on OpenAlex
Zohra Surani, Gillian Strudwick, Linda Purushuttam, Rani Srivastava

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueNursing leadership · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAppreciative Inquiry and Organizational Change
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsAppreciative inquiryNursingMental healthAddictionPsychologyProcess (computing)Nurse managerMedicinePsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Feelings of empowerment in nursing staff can contribute to increased job satisfaction, improved quality of care and a higher retention rate within healthcare organizations. Nursing is critical at healthcare organizations, with direct and significant impact on the quality of care provided; yet, nurses often feel undervalued for the work they do. The strength-based approach of appreciative inquiry is one way to engage individuals in finding collective value through the identification of successes, enabling the creation of a shared vision and strategy for the future.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.127
GPT teacher head0.325
Teacher spread0.198 · 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