Social participation needs of older adults in an urban revitalization: results from participatory action research during the COVID-19 pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Adults aged 80 or older, with a low income, with a disability, or belonging to ethnic, linguistic, sexual or gender minorities are particularly at risk of exclusion, especially during neighborhood revitalizations and pandemics. This study aimed to document individual and collective needs, facilitators and barriers to social participation of older residents and users of downtown Sherbrooke (Quebec, Canada) at risk of marginalization during an urban revitalization. We used a participatory action research design with 32 older adults, 1 caregiver and 5 community partners. Participants expressed high expectations regarding the downtown revitalization. Individual and collective social participation needs were identified, particularly relating to inclusive environments, i.e. adapted, safe, clean and healthy; with access to activities, resources, affordable transportation and housing; accompanied to participate in activities; and informed about social participation opportunities. Main facilitators were health, income, public space designed to promote social interaction, activities offered, assistance of family and friends, and security. Obstacles were disabilities, precarious living conditions, COVID-19 restrictions and discrimination. The pandemic made collaborative research difficult, which triggered new strategies (e.g. media watch, research newsletter). Results could improve the development of a downtown area, inclusive for all older adults, and inspire future projects to leverage the power of communities.
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.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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 it