Creating space for citizenship: The impact of group structure on validating the voices of people with dementia
Bibliographic record
Abstract
Recently, there has been increasing attention given to finding ways to help people diagnosed with dementia 'live well' with their condition. Frequently however, the attention has been placed on the family care partner as the foundation for creating a context that supports the person with dementia to live well. A recent participatory action research (PAR) study highlighted the importance of beginning to challenge some of the assumptions around how best to include family, especially within a context of supporting citizenship. Three advisory groups consisting of 20 people with dementia, 13 care partners, and three service providers, were set up in three locations across Canada to help develop a self-management program for people with dementia. The hubs met monthly for up to two years. One of the topics that emerged as extremely important to consider in the structuring of the program revolved around whether or not these groups should be segregated to include only people with dementia. A thematic analysis of these ongoing discussions coalesced around four inter-related themes: creating safe spaces; maintaining voice and being heard; managing the balancing act; and the importance of solidarity Underpinning these discussions was the fifth theme, recognition that 'one size doesn't fit all'. Overall an important finding was that the presence of family care-partners could have unintended consequences in relation to creating the space for active citizenship to occur in small groups of people with dementia although it could also offer some opportunities. The involvement of care partners in groups with people with dementia is clearly one that is complex without an obvious answer and dependent on a variety of factors to inform a solution, which can and should be questioned and revisited.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".