Associational Capital and Adult Charitable Giving: A Canadian Examination
Bibliographic record
Abstract
This article examines the relationship between associational capital, developed through participation in social networks, and charitable giving behavior in Canada. Empirical models are specified to determine whether a relationship exists between associational capital, formed in youth and adulthood, and secular and religious donation expenditures in adulthood. Tobit regression models are estimated using data from the 2010 Canada Survey of Giving, Volunteering and Participating (CSGVP). The results suggest that the formation of associational capital in youth and adulthood is related to larger donation expenditures, although the source of associational capital and the type of recipient organization matters. It is also found that those who participate in a variety of associations are more likely to make larger donations than those who participate in fewer types of associations. The results provide further insight into charitable giving behavior and have policy implications for public and nonprofit sectors concerned with increasing charitable donations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".