CULTURAL MOTIVATION TO VOLUNTEER AMONG OLDER JEWISH ADULTS: AN EXPLORATORY STUDY
Bibliographic record
Abstract
Abstract The physical, mental, and social benefits for older adults who volunteer are well-documented. Absent from this area of research however, is an understanding of volunteer motivation and experiences among culturally diverse older adults. This study addresses this research gap by exploring the volunteer pathways, motivations, and experiences of Jewish older adults in Vancouver, BC, Canada. The Jewish community is notable for possessing high levels of social capital, indicated by close community ties and the large number of faith and culturally based organizations, including community centres, day schools, seniors’ centres, and family service agencies, which provide many opportunities for older adults to volunteer. Despite this, they remain an understudied population. Semi-structured qualitative interviews were conducted with twenty-one older adult volunteers (age 55+), and two paid volunteer staff in the Jewish community. Theoretical concepts including social capital, generativity, and the life course perspective on aging were used to guide interview questions. Data analysis revealed three themes related to cultural motivation to volunteer: 1.) A desire to support the current and future generations of the Jewish community, 2.) To satisfy the “Jewish ethic” of giving back, and 3.) Experiences of discrimination (anti-Semitism) over the life course. Participants frequently volunteered for organizations that supported the infrastructure of the Jewish community. Findings indicate how cultural experiences and values may influence the decision to volunteer and the types of volunteer roles taken on by older adults. Further, they suggest the ways in which cultural and religious generativity may be expressed through volunteerism, a previously unexplored concept.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".