Ageing, place and voluntarism: towards a geographical perspective on third sector organisations and volunteers in ageing communities
Bibliographic record
Abstract
This article addresses the gap within discourses on ageing that call for greater involvement of the third sector in support of older people, but do not account for the difference ‘place’ makes to understanding third sector activities and volunteering. It reviews recent developments in the literature that highlight the importance of place-based approaches, particularly the emergent view of voluntarism as a transformative process that shapes and is shaped by the interactions between older people and their ageing communities. The link between ageing, place and voluntarism is illustrated via a case study of volunteer-based community support for older people in Canada’s most rapidly ageing municipality. Findings from an inventory, survey, focus groups and interviews in Peterborough, Ontario reveal the complexity, interdependence and place-embeddedness behind a successful yet potentially unsustainable response to the challenge of supporting older people. The paradox of relying on under-resourced third sector organisations and older volunteers is highlighted.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 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".