<i>Dementia Without Borders</i> : Building community connections to reduce stigma and foster inclusion
Bibliographic record
Abstract
Around the world people with dementia face stigma and social exclusion. An interdisciplinary team from Seattle, Washington, and Vancouver, British Columbia led a collaborative project developing cross-border community partnerships to increase awareness and reduce stigma, promote social participation of people with dementia, and enhance their well-being. The work was organized around three themes - citizen engagement, social entrepreneurship, and creative expression – and involved regular meetings so researchers, community providers, and people with dementia and care partners could know each other better. Dementia Without Borders was organized as an end-of-project celebration, a public festival bringing together community members from both countries to share what the team had learned from each together. The event took place at the Peace Arch, an international park straddling the border between Washington and British Columbia. Over 140 people arrived on their respective sides, created banners, and walked together to the Peace Arch to meet and exchange gifts with those coming from the other country. A picnic shelter was used to display art created by people with dementia and outdoor tables allowed everyone to eat together and listen to poetry readings and musical performances. Feedback was overwhelmingly positive with many expressing a sense of hope and belonging. This project has leveraged the symbolic power of an international border to generate new ideas about fostering social inclusion and reducing stigma for people with dementia. It shows the importance of place and history, building relationships on trust and participation, and being flexible and responsive to opportunities for social innovation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".