Navigating Complex Implementation Contexts: Overcoming Barriers and Achieving Outcomes in a National Initiative to Scale Out Housing First in Canada
Bibliographic record
Abstract
The scaling out of Housing First (HF) programs was examined in six Canadian communities, in which a multi-component HF training and technical assistance (TTA) was provided. Three research questions were addressed: (a) What were the outcomes of the TTA in terms of the development of new, sustained, or enhanced programs, and fidelity to the HF model? (b) How did the TTA contribute to implementation and fidelity? and (c) What contextual factors facilitated or challenged implementation and fidelity? A total of 14 new HF programs were created, and nine HF programs were sustained or enhanced. Fidelity assessments for 10 HF programs revealed an average score of 3.3/4, which compares favorably with other HF programs during early implementation. The TTA influenced fidelity by addressing misconceptions about the model, encouraging team-based practice, and facilitating case-based dialogue on site specific implementation challenges. The findings were discussed in terms of the importance of TTA for enhancing the capacities of the HF service delivery system-practitioners, teams, and communities-while respecting complex community contexts, including differences in policy climate across sites. Policy climate surrounding accessibility of housing subsidies, and use of Assertive Community Treatment teams (vs. Intensive Case Management) were two key implementation issues.
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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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".