The Korean Canadian experience of caregiver burden
Bibliographic record
Abstract
Even though Canadian society is becoming more diverse in its cultural composition, there have been few studies that examine cultural differences of caregiver burden of older adults. This study investigated the Korean-Canadian experience of caregiver burden. It explored how the background characteristics of caregivers and care recipients, caregiving practice, social service utilization, motive and rewards of caregiving, and levels of caregiver depression and life satisfaction influenced caregiver burden. In particular, self-reported national identity, a proxy for the degree of acculturation, was a key independent variable. Fifty-seven Korean-Canadian primary caregivers in the Greater Toronto Area, Hamilton, Cambridge, and Kitchener-Waterloo participated in the study. Using multiple regression methods, data were examined to derive a conceptual model of the Korean-Canadian Caregiver Burden experience. Caregiver's marital status and self-reported national identity were significant predictors of caregiver burden. Married Korean-Canadian caregivers felt more burdened than their non-married counterparts. Those Korean-Canadian caregivers who identified with Canadian nationality felt more burdened than those who identified with Korean nationality. This result may indicate that the former group may be more acculturated to Canadian society and its value system than the latter group. This research supports that cultural influence and acculturation may lead to differences in caregiving experiences even among members of the same ethnic group.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".