Combatting Homelessness in Canada: Applying Lessons Learned from Six Tiny Villages to the Edmonton Bridge Healing Program
Bibliographic record
Abstract
Emerging evidence shows that homelessness continues to be a chronic public health problem throughout Canada. The Bridge Healing Program has been proposed in Edmonton, Alberta, as a novel approach to combat homelessness by using hospital emergency departments (ED) as a gateway to temporary housing. Building on the ideas of Tiny Villages, the Bridge Healing Program provides residents with immediate temporary housing before transitioning them to permanent homes. This paper aims to understand effective strategies that underlie the Tiny Villages concept by analyzing six case studies and applying the lessons learned to improving the Bridge Healing Program. After looking at six Tiny Villages, we identified four common elements of many successful Tiny Villages. These include a strong community, public support, funding with few restrictions, and affordable housing options post-graduation. The Bridge Healing Program emphasizes such key elements by having a strong team, numerous services, and connections to permanent housing. Furthermore, the Bridge Healing Program is unique in its ability to reduce repeat ED visits, lengths of stay in the ED, and healthcare costs. Overall, the Bridge Healing Program exhibits many traits associated with successful Tiny Villages and has the potential to address a gap in our current healthcare system.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".