On the prospect and precarity of rural older voluntarism
Bibliographic record
Abstract
Volunteers are essential to supporting vulnerable older people in underserviced communities. Evidence is emerging, however, of the growing precarity of volunteering in small towns and rural places where most volunteers are older residents themselves. To advance knowledge on this phenomenon of ‘rural older voluntarism’, particularly in the context of the COVID-19 pandemic, this article presents a case study of three volunteer-based programs in rural Ontario, Canada. Interviews and focus group discussions with 56 volunteers and program administrators reveal both the prospect and precarity of rural older voluntarism, shedding light on how the pandemic acted as a catalyst of change for individual volunteers, volunteer-based programs and ageing rural communities alike. Learning from the experiences both of older volunteers and administrators at volunteer-based programs in ageing rural communities can advance best practices for future-proofing the pivotal role of voluntarism for communities undergoing unprecedented changes such as natural disasters, economic upheaval and public health emergencies.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".