KEY DIMENSIONS OF OASIS, AN OLDER-ADULT DRIVEN MODEL OF AGING-IN-PLACE IN CANADA
Bibliographic record
Abstract
Abstract Oasis Senior Supportive Living (Oasis) is an active aging-in-place model created by older adults in a naturally occurring retirement community, such as an apartment building. The program is member-driven so that participating older residents determine the programming and services that best address their needs. The first Oasis program was established in an apartment building in Kingston, Canada and has been running for more than ten years. Preliminary evaluations of the Oasis program demonstrate that its members report feeling more socially connected, are more physically active, and have increased nutrition as a result of participation. In-depth interviews were conducted with Oasis members and key program stakeholders to identify the core dimensions of the Oasis program that has led to its success in supporting active aging in place. Interviews were audio-recorded and transcribed verbatim. Thematic analysis was used to identify, analyze and report themes. Four themes emerged: (1) nutrition, social and physical activities as critical programming pillars; (2) the importance of active member participation and decision-making; (3) the need for onsite support to facilitate programming; and (4) Oasis as a family. These findings highlight the need for programming that is designed for and by older adults. Supporting older adults to come together and form community is key to healthy and active aging. Identification of these elements is critical to modelling Oasis in other community contexts. Oasis is currently being expanded to seven new communities across Ontario using a participatory action research approach.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| 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".