Economics of Intergenerational Volunteering: A Mixed-Methods Study of Snow-Buddies Program in Niagara Region, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the financial costs and savings of a community-based intergenerational volunteer program (i.e. Snow-buddies) that pairs youth with older adults for snow removal. From March 2020 to May 2023, Snow-buddies completed 106 volunteer-matches and 486 snow removal events. Using a sequential exploratory mixed-method design, 14 semi-structured interviews were conducted with youth volunteers and older adults. The majority of participants revealed minimal out-of-pocket (OOP) expenses and time/productivity losses for snow removal. Increased mobility, fall prevention, and social connections were perceived benefits of the program. A survey (n = 55, 52% of matched participants) reported an average CAD$123 OOP spending per snow removal event. Applying the rate of fall injuries among older adults due to snow, an estimated 1.12 fall injuries per 486 person-events were prevented translating into a total of $81,398 financial savings from averted hospitalization (i.e. a benefit–cost ratio of ~$662 for every dollar spent on snow removal).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it