Altruistic behaviour and social capital as predictors of well-being among older Canadians
Bibliographic record
Abstract
ABSTRACT Self-reported altruistic activity and social capital were examined as predictors of perceived happiness and life satisfaction among a sample of 4,486 Canadians aged 65 or more years from the 2003 Canadian General Social Services Survey , Cycle 17. Altruistic behaviour was measured by number of volunteer hours per month and helping others (not including family and friends). Social capital was measured using dimensions of belonging to one's community, community and neighbour trust, and group activities. Drawing on generativity and role-identity theories, it was hypothesised that altruistic behaviour and social capital are positively associated with well-being (using perceived happiness and life satisfaction), and that social capital mediates the relationship. For both perceived happiness and life satisfaction, after controlling for demographic, health status, and social support variables, measures of altruistic behaviour demonstrated statistically significant associations. Once measures of social capital were entered into the analysis in the final block, however, the altruistic behaviour variables were no longer statistically significant. Robust associations were found for social capital and the two measures of well-being, particularly between sense of belonging, trust in neighbours, and perceived happiness and life satisfaction. The findings suggest that altruistic behaviour is mediated by social capital. The implications of these findings are discussed with respect to understanding the well-being of older Canadians.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".