Time Banking and Health: The Role of a Community Currency Organization in Enhancing Well-Being
Bibliographic record
Abstract
Time banking is an international movement that seeks to transform traditional asymmetric social service models into social networks in which members both provide and receive services that are assigned equal value. Time banks have been shown to enhance social capital, and there is some evidence for improved health. This article, based on a survey of 160 members of a hospital-affiliated time bank, examines the likelihood and predictors of improvement in physical and mental health as a result of membership. Men, people with lower income, and those who were not working full-time reported highest levels of participation in exchanging services; attachment to the organization was greatest among women, older members, people with less education, and those with the highest participation levels. Multivariate analyses revealed that physical health improvement attributed to membership was significantly predicted by attachment to the organization and living alone; mental health gains were predicted by general health changes, average number of exchanges, and attachment to the organization. We conclude that a sense of belonging, a dimension of social capital, is key to improved well-being and that time banking may be particularly valuable in promoting health and belonging among older and lower-income individuals and those who live alone.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".