Students and Seniors: Intergenerational Homesharing in Kingston, Ontario
Bibliographic record
Abstract
As Ontario’s aging population increases, so do reports of loneliness and social isolation amongst seniors. Local-level strategies to curb loneliness amongst seniors have the potential to improve the health and well-being of seniors – and incidentally, the well-being of students. Student-senior homesharing draws students and seniors into a mutually-beneficial intergenerational living arrangement, where seniors gain social interaction and students secure affordable rental housing. By drawing insight from student-senior homesharing programs that have been adopted in Hamilton and Toronto, this report examines the potential viability of homesharing between students and seniors in Kingston. This research contributes to an overarching discussion on intergenerational living by providing additional insight into student-senior homesharing, and offering research-based recommendations that can be applied in the development of a student-senior homesharing program in Kingston. A multi-level case study was employed using a mixed-methods approach to data collection, utilizing an online survey to capture the perspectives of Queen’s University graduate students on the student housing market and attitudes towards intergenerational living. Interviews with local informants explored attitudes towards, and need for, student-senior homesharing in Kingston, and interviews with informants from Hamilton and Toronto gaged the conditions for successful project implementation. The research findings demonstrate that loneliness and a difficult rental market serve as conditions for implementing a student-senior homesharing project. Despite these conditions occurring in Kingston, the majority of graduate students are not interested in living with a senior. Interest in living with a senior is highly variable and personal, but can be predicted by a number of factors. While student-senior homesharing projects occur at a small scale, the human connection generated within the community makes these projects highly valuable, providing a variety of benefits and opportunities to both students and seniors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".