Examining peer networking as a capacity‐building strategy for Housing First implementation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: This study examines peer networking as a capacity-building strategy for the implementation of Housing First (HF), a complex community intervention targeting chronic homelessness. METHODS: A qualitative, multiple case study was conducted to examine the capacity-building activities of two, multicommunity peer networks established by community leaders in the Canadian Homelessness sector. Data collection activities included document analysis, key informant interviews (n = 10), and a follow-up focus group with interview participants in each network. Thematic analyses were conducted for each network, followed by a cross-case analysis. RESULTS: Engaging in a multicommunity peer network enhances leaders' capacity to advance HF by creating opportunities to foster trust and communication, inform continuous improvement, and navigate ambiguity. A number of contextual factors influence connections between peer networking and capacity building. CONCLUSION: Peer networks are a valuable source of support and timely, contextually relevant knowledge for community leaders advancing local adaptation and implementation of HF.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it