Thriving-in-Place: Examining the impact of intergenerational living in the Toronto HomeShare Program
Bibliographic record
Abstract
Abstract Most global cities, like Toronto, have rapidly aging populations who want to remain in homes and communities of their choice. Concurrently, seniors face vulnerabilities associated with low income, ageism, social isolation and loneliness. These vulnerabilities inhibit many seniors’ desires to age-in-place. The Toronto HomeShare Program, an intergenerational homesharing program facilitates aging-in-place by matching seniors with post-secondary students. The program, with an implementation focus and a research study, was developed to address and understand the needs of seniors seeking assistance, light supports and companionship at home, in exchange for reduced-rent housing for students. A mixed methods research design was employed. Seniors and students (n=22) completed a 167 question survey (n=22) and in-depth interviews (n=18). Quantitative data yielded descriptive statistics and qualitative data was subject to thematic content analysis. Participants agreed that homesharing programs could address risk for social isolation (95%), the need to move from their community (96%), and reduce risks of economic and social exclusion for young and old (97%). From the qualitative data, six benefits were apparent for all participants: (1) reduced social isolation and loneliness, (2) increased intergenerational exchange, (3) increase financial security, (4) household assistance, (5) increased general wellbeing; (6) enhanced companionship/safety. In 2020, Toronto HomeShare (now Canada HomeShare) was recognized by the World Health Organization as an age-friendly best practice, and has been scaled nationally in 16 cities. Intergenerational homesharing programs could be a catalyst for policy and cultural reform and to support older adults to not only remain in their communities, but to thrive-in-place.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 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".