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Record W2105813104 · doi:10.1177/1471301213518935

Theoretical foundations guiding culture change: The work of the Partnerships in Dementia Care Alliance

2014· article· en· W2105813104 on OpenAlexafffundabout
Sherry L. Dupuis, Carrie McAiney, Darla Fortune, Jenny Ploeg, Lorna de Witt

Bibliographic record

VenueDementia · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAppreciative Inquiry and Organizational Change
Canadian institutionsUniversity of WindsorMcMaster UniversityUniversity of Waterloo
FundersAlzheimer Society
KeywordsAppreciative inquiryAllianceCulture changeGeneral partnershipDementiaAction (physics)Organizational cultureParticipatory action researchCitizen journalismPublic relationsSociologyWork (physics)Theory of changePsychologyPolitical scienceMedicineDiseasePedagogySocial scienceEngineering

Abstract

fetched live from OpenAlex

Longstanding concerns about quality care provision, specifically in the area of long-term care, have prompted calls for changing the culture of care to reflect more client-driven and relationship-centred models. Despite an increase in culture change initiatives in both Canada and the United States, there is insufficient information about the theories and approaches that guide culture change. The purpose of this paper is to describe a culture change initiative currently underway in Canada, the Partnerships in Dementia Care Alliance, and the theoretical foundations informing our work. More specifically, we describe how the theoretical and philosophical underpinnings of the Alzheimer Disease and Related Dementias framework, the authentic partnership approach, participatory action research and Appreciative Inquiry have been integrated to guide a culture change process that encourages working collaboratively, thinking and doing differently and re-imagining new possibilities for changing the culture of dementia 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)0.050
metaresearch head score (Gemma)0.038
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: none
Teacher disagreement score0.050
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0280.129
Scholarly communication0.0290.018
Open science0.0040.020
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0040.001

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 head0.082
GPT teacher head0.268
Teacher spread0.186 · 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

Citations80
Published2014
Admission routes3
Has abstractyes

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