Learning to respect our elders: aging-in-place modifications in Toronto community housing
Bibliographic record
Abstract
This paper examines the feasibility of seniors physically aging-in-place within Toronto Community Housing Corporation’s (TCHC) portfolio. Due to the demographic shift that the City of Toronto and TCHC will experience in the upcoming decades, there will be a greater need to ensure that tenants are provided with safe accommodations to foster aging-in-place. Being able to provide this to senior tenants will require that several modifications be made to units, and tenants and TCHC will share this responsibility. These modifications must comply with the policies in place, and be feasible within constrained budgets. This research outlines the key unit modifications required for aging-in-place to occur, and highlights their costs and impact on tenants and TCHC, which ultimately helps determine the feasibility of implementing aging-in-place modifications. The imperative on tenants, TCHC and higher orders of government is detailed so they can take proactive measures in accommodating for this subset of 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".