Intergenerational Dance in Long-Term Residential Care: Social Citizenship in Dementia Care
Bibliographic record
Abstract
To view the accompanying Digital Story, visit: https://bcstudies.com/digital_stories/dance/ Older adults living with dementia in long-term residential care homes present complex care challenges related to their cognitive, communication, and functional losses. Their enduring potential and abilities are often obscured by a focus on their deficits and disabilities. As a result, care staff struggle to ensure their quality of life and well-being. Reductionist views support assumptions that residents living with dementia have limited ability to participate in, and benefit from, meaningful activities and relationships. Negative views and diminished opportunities for engagement effectively strip these residents of their personhood and citizenship. In recent decades a broader view of persons living with dementia has emerged, recognizing their enduring potential for meaningful engagement; and, increasingly the arts have been explored in dementia care programming to support meaningful engagement. Our six-month research study highlights the enduring capacity for inclusion and engagement experienced by residents living with dementia through their participation in an innovative intergenerational dance program in British Columbia’s Lower Mainland. Imagine Dance blends elements of dance movement therapy with intergenerational programming, partnering school-aged children with residents living in long-term residential care homes in ballet classes. Through partnering with the children and working towards shared goals in weekly dance classes, the residents in our study formed relationships and found community. Our findings support the potential that arts-based programming holds for providing meaningful engagement and promoting social citizenship for people living with dementia in long-term residential care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".