Resilience in Japanese Older Immigrants in Canada and the Role of Community Support During the COVID-19 Pandemic
Bibliographic record
Abstract
Japanese people make up a small proportion of the population in Canada, and there are limited resources to meet their specific needs. Thus, older Japanese Canadians were particularly affected by disrupted support and service systems when COVID-19 public health orders were implemented. The objective of this study was to explore how Japanese older immigrants cultivated resilience in overcoming challenges during the COVID-19 pandemic and how a community service agency supported the process. In this qualitative study, seven community-dwelling Japanese older immigrants and five agency staff participated in semi-structured interviews. Interviews were thematically analyzed using a conceptual lens of resilience, which refers to the ability to survive and thrive in the face of adverse life experiences. Our analysis yielded three themes: (1) Challenges and concerns associated with digital literacy, English literacy, COVID-19, and the future; (2) Individual sources of physical, mental, and social resilience; and (3) Agency-supported sources of resilience that enable management of health, safety, and daily life, connection, and belonging. The findings advance our understanding of the ways in which older immigrants cultivate resilience in the face of adversity and how programs and services can help older immigrants cope with adversity to meet their needs. Implications for service provision include ensuring systems are in place to digitally connect older adults to programs, support home maintenance and housekeeping, and engage older adults in the development of new programs.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".