Toward the Right to Housing in Canada: Lived Experience, Research, and Promising Practices for Deep Engagement
Bibliographic record
Abstract
Canada’s 2019 Housing Strategy Act (NHSA) lays the groundwork for important advances in ensuring the right to housing for all. Two key approaches outlined in the NHSA for communities in greatest need are conducting research and providing participatory ways for those communities to shape housing rights responses. This article presents insights from a project that explored how people with lived experience of housing need and homelessness engage in research on housing precarity in Canada. We review the literature on housing precarity that features people with lived experience as research participants, applying an intersectional framework and acknowledging the settler colonial context of Canada. And, as a research team who has members with lived experiences of housing precarity, we emphasize the importance of meaningfully incorporating people’s lived experiences, seeing deep engagement as a way to advance housing rights by harnessing lived knowledges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.697 | 0.255 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.194 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.388 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".