Competing challenges for immigrant seniors: Social isolation and the 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
The pandemic has exposed and amplified complex and complicated health and societal challenges while offering immense opportunities to transform societies to improve health for all. Social isolation is a challenging and persistent issue experienced by many older adults, especially among immigrant and refugee seniors. Unique risk factors such as racism, discrimination, language barriers, weak social networks, and separation from friends and family predispose immigrant and refugee seniors to a higher risk of social isolation. The pandemic has magnified the unique risks and has highlighted the differential health and economic impacts. This article examines social isolation among immigrant and refugee seniors in Canada by focusing on the policy context, available programs and services to reduce social isolation, and the conceptualization and measurement considerations for advancing research to address social isolation among this growing population. Drawing on specific examples, we discuss immigration, aging, and social isolation within the context of Canada. While our article focuses on Canada as a case study, our discussion has relevancy and implications for other high-income countries with aging immigrant and refugee populations. In moving forward, we argue that a more complete and targeted understanding of social isolation is essential to informing program and policy development to support immigrant and refugee seniors in Canada and beyond. The transformation needed in our societies to create health for all requires strong equity and determinants of health perspective and a systems approach beyond health to ensure lasting change.
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 | 0.001 | 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 | 0.002 | 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