Examining Social Relationships among Older Muslim Immigrants Living in Canada: A Narrative Inquiry
Bibliographic record
Abstract
Social connectedness and engagement are particularly important among groups who are at risk of experiencing social isolation, such as immigrant older adults. The objective of our study was to understand the social relationships of aging Muslim Lebanese immigrants living in Canada by exploring their lives in their ethnic and wider communities. This study used a life course perspective and adopted a constructivist narrative inquiry to understand the diverse lived experiences of four older adults who immigrated to Canada during early adulthood. Participants engaged in a narrative interview and follow-up session in which they storied their lived experiences. Findings describe one core theme, cultivating social relationships through family, friends, and community interdependence, and three related sub-themes: (1) navigating and creating family interdependence and planting new roots; (2) family interdependence in later life: the important role of grandchildren; and (3) cultivating ethnic and local interdependence to support aging in place. The participants’ stories provided an understanding of how culture, religion, aging, family, and immigration experiences interrelated throughout their life course and shaped their social relationships during later life. This study sheds new insight on the importance of culturally tailored activities and awareness about the social needs of immigrant older adults.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".