Oasis Senior Supportive Living: Description of a Novel Aging-in-Place Model in Ontario
Bibliographic record
Abstract
Older adults are the fastest-growing demographic group in Canada, and the majority of older adults want to age-in-place within their communities. Many older adults live in naturally occurring retirement communities (NORCs), unplanned communities with a high proportion of older residents. NORC supportive services programs can help older adults successfully age-in-place. One such program is Oasis Senior Supportive Living, a partnership between older adults, building owners and managers, community partners, funders, and researchers. Using a qualitative approach, interviews were conducted with Oasis participants to understand their experiences of Oasis. This article will describe the three pillars upon which Oasis programming is based and provide insights from Oasis participants. It will discuss nutrition programming implemented in these NORCs and suggest how dietitians can support NORC residents.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".