Aging in community: the case of Hesperus village in Vaughan in Ontario, Canada
Bibliographic record
Abstract
This study focuses on the evolving notion of aging in community, by presenting findings of a qualitative, descriptive study conducted in Hesperus Village, a unique community for predominantly older adults located in Vaughan in Ontario, Canada. The purpose of this exploratory study was to gauge the benefits and challenges of aging in community, and develop conceptualization of the nature and form of attached social relationships and community concerns. Eight semi-structured, in-depth interviews with open-ended questions of residents and a manager were conducted. Findings indicated that aging in this community included a mix of resident co-caring and formal caring practices; that traditional forms of management style are shifting to democratic self-governance practices and that forging links with the wider community is linked to the sharing of resources and inter-generational bartering of services. The implications of aging in community point toward the notion of social responsibility as a potential strategy toward sustainable practices; and that sharing resources with the wider community may have cost-saving implications. This study serves as a call for further research and advocacy in addressing an all-encompassing service delivery model to age in community from birth until death, linking aging in place and dying in place agendas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".