Making a university community more dementia friendly through participation in an intergenerational choir
Bibliographic record
Abstract
A dementia friendly community is one that is informed about dementia, respectful and inclusive of people with dementia and their families, provides support, promotes empowerment, and fosters quality of life. This study presents data from four cohorts of undergraduate college students and people with dementia and their family members, using an intergenerational choir as the process through which to begin to create a dementia friendly community. This was accomplished by breaking down the stereotypes and misunderstandings that young adults have about people with dementia, thus allowing their commonalities and the strengths of the people living with dementia to become more visible. Data were gathered for each cohort of students through semi-structured open-ended questions on attitudes about dementia and experiences in the choir, collected at three points over 10 weeks of rehearsals. Data about their experiences in the choir were collected from each cohort of people with dementia and their family members through a focus group. Results across all four cohorts showed in the students: changed attitudes, increased understanding about dementia and the lived experience, reduced dementia stigma, and the development of meaningful social connections. People with dementia and their family members expressed feelings of being part of a community.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".