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Record W4386045819 · doi:10.1002/gps.5984

Making space at the table: Engaging participation of people with dementia in community development

2023· article· en· W4386045819 on OpenAlexafffundabout
Alison Phinney, Eric Macnaughton, Elaine Wiersma, Nisha Sutherland, Carlina Marchese, Diana Cochrane, Andrea Moreira Monteiro

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2023
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsLakehead UniversityUniversity of British Columbia
FundersPublic Health Agency of Canada
KeywordsDementiaCitizen journalismFocus groupInclusion (mineral)Participatory action researchPublic relationsAsset (computer security)SociologySpace (punctuation)Work (physics)Community developmentPsychologyPolitical scienceMedicineGender studiesEngineeringDisease

Abstract

fetched live from OpenAlex

OBJECTIVES: The Building Capacity Project is an asset-based community development initiative that aims to reduce stigma and promote social inclusion for people with dementia. Using a community-based participatory approach, we conducted research to examine the relational patterns and participatory practices within and across project sites in two different regions of Canada (Vancouver and Thunder Bay). METHODS: Five focus groups and five individual interviews were conducted with team members and community partners (n = 29) and analysed for themes. RESULTS: The overarching theme of Making Space at the Table explains how the participation of people with dementia has served both as a value and a practice shaping the relational work throughout the project. Three sub-themes include: Maintaining a common foundation; Creating communication pathways; and Fostering personal connections. CONCLUSIONS: Together, these findings show how community development can support the meaningful participation of people with dementia in their communities through processes of collaboration that focus on individual and collective strengths, that allow time for the work to unfold, and for building relationships that foster trust and respect for diversity.

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)0.004
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 score0.012
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.071
GPT teacher head0.432
Teacher spread0.361 · 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

Citations4
Published2023
Admission routes3
Has abstractyes

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