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Work empowerment in multidisciplinary teams during organizational change

2009· article· en· W2140427202 on OpenAlexaff
Sirkku Rankinen, Tarja Suominen, Liisa Kuokkanen, Marja Leena Kukkurainen, Diane Doran

Bibliographic record

VenueInternational Journal of Nursing Practice · 2009
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmpowermentMultidisciplinary approachWork (physics)Organization developmentOrganizational changePsychologyNursingHealth careOrganizational commitmentMedicinePublic relationsSociologyPolitical scienceSocial psychologyEngineering

Abstract

fetched live from OpenAlex

Conducted as part of a project dealing with work empowerment in multidisciplinary teams in a Finnish hospital specializing in providing care and treatment for different rheumatic conditions, this study set out to explore the associations between organizational change factors and perceived work empowerment in a setting where patients with chronic diseases are being cared for by multiprofessional teams. All health‐care professionals working at the hospital under investigation were invited to take part in the survey. Data were collected in 2005 with a structured questionnaire consisting of five parts: background variables, organizational change factors, aspects of work empowerment as well as factors promoting and impeding empowerment. Organizational change factors correlated with work empowerment as well as factors promoting and impeding empowerment. There was little agreement by multiprofessional teams that factors relating to organizational change were present in their work setting. Organizational change factors are important in order to be able to meet the demands by facilitating optimal action during organizational changes. The planning and implementing of organizational changes should be performed in cooperation with personnel throughout the organization at all stages. It would be important to address potential difficulties and try to pre‐empt any problems from the planning stage.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.047
GPT teacher head0.505
Teacher spread0.458 · 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 designObservational
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

Citations18
Published2009
Admission routes1
Has abstractyes

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