New Solutions for “Old” Problems: Implications and Opportunities of Intergenerational HomeSharing
Bibliographic record
Abstract
Abstract Across North America, many older adults have expressed their preference to live in their own homes and communities for as long as possible — and to 'age in place'. To address challenges faced by older adults living in the community, home-sharing - an exchange-based intergenerational housing approach, has empowered older adults to ‘thrive in place’ by providing additional income, companionship, and support with household tasks. In 2018, Toronto HomeShare was launched as an intergenerational home-sharing pilot program (n=22), matching older adults (55+) with postsecondary students intending to simultaneously address social isolation and the affordable housing crisis. In 2019, the pilot was adopted as a funded program in the City of Toronto with over 200 participants. Program results highlight unique benefits and challenges for older adults participating in home-sharing: (1) the capacity for intergenerational engagement to fulfill social needs, and (2) the importance of agency facilitation as a determinant of the experience for older adults. Survey findings indicate 88% of participants reported that participation in HomeShare positively impacted their general well-being, 88% reported improved financial security, 94% reported a delay in the need to move out of their community, and 72% felt that participation in HomeShare prevented the need for institutional care. These findings were used to transition Toronto HomeShare into a fully funded program as well as in the development of a national program. Beginning in January 2021 Toronto HomeShare transitioned to Canada HomeShare and will be scaling the program to Vancouver, Winnipeg, Halifax, Calgary, Montreal and other Canadian cities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".