Systems change in the context of an initiative to scale up Housing First in Canada
Bibliographic record
Abstract
In this study, we examine changes in the homeless-serving system in the context of a training and technical assistance initiative to scale up Housing First (HF) in 6 Canadian communities. Based on qualitative data from focus groups and individual interviews with key stakeholders (k = 7, n = 35) and field notes gathered over a 3-year period (n = 146), we found 2 main system changes: (a) changes in the capacity of the service delivery system at multiple levels of analysis (from individual to policy) to implement HF, and (b) changes in the coordination of parts of the service delivery system and collaboration among local stakeholders to enhance HF implementation. These changes were facilitated or constrained by the larger context of evidence, climate, policy, and funding. The findings were discussed in terms of systems change theory and implications for transformative systems change in the mental health and homelessness sectors.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".