Designing for tenant wellbeing : a new approach to Canadian social housing
Bibliographic record
Abstract
Increased focus on non-housing outcomes in the context of social housing in Canada continues. However, that focus remains predicated on existing systems, for the most part designed in the mid to late 1990s. To really support tenants of social housing, we need to create systems that will put the people first. To that end, this dissertation asks the question of how best to design a social housing system in Canada that facilitates and enhances tenant wellbeing. After providing a review of the evolution of social housing policy in Canada, this dissertation then introduces a definition for tenant wellbeing based on the Capability Approach, consisting of six domains: self-determination, health, belonging, security (cultural, tenure, and financial), controlling one’s space, and quality of life. This definition was then used in the analysis of the findings from comparing the systems in British Columbia, Alberta, Saskatchewan, and Manitoba based on each respective system environment, boundary, system elements and their interconnections, and system function. Those findings were supplemented by interviews with senior executives working in each province. After identifying different parts of the existing systems that facilitate or disempower tenant wellbeing, the dissertation outlines the principles based recommendations to design a new social housing system focused on tenant wellbeing, and how this idea may come to fruition in the current policy and regulatory environment.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.022 | 0.026 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".