The Lived Experiences of Spousal Bereavement and Adjustment Among Older Chinese Immigrants in Calgary
Bibliographic record
Abstract
Spousal bereavement poses considerable challenges to adults in late life. Some populations, such as older immigrants, may experience heightened negative outcomes as a consequence of spousal bereavement, due to migratory stress and social isolation. Spousal bereavement is culturally embedded as it is related to cultural beliefs and attitudes concerning death and family relationships. However, studies on spousal bereavement or widowhood among older immigrants are extremely limited. This study aims to fill the gap by exploring, via a phenomenological approach, the lived experiences of widowed older Chinese immigrants in Calgary and responding to the question: What are the lived experiences of widowed Chinese older immigrants in coping with their spousal bereavement? With the data drawn from 12 in-depth qualitative interviews, findings were categorized into individual, family, community and societal levels. Study participants experienced long-lasting grief that was private and impacted by their culture and immigration status. Although family and ethno-cultural communities provided various types of supports during participants' widowhood, they did not directly assist them in coping with spousal loss. Most participants did not access social services for bereavement support, more often relying on cultural rituals and faith practices. Findings suggest the need for culturally appropriate bereavement supports and family/community involvement for older immigrant adults who have experienced spousal loss.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| 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".