An intervention strategy for improving residential environment and positive mental health among public housing tenants: rationale, design and methods of Flash on my neighborhood!
Bibliographic record
Abstract
BACKGROUND: In Canada, public housing programs are an important part of governmental strategies to fight poverty and public exclusion. The Flash on my neighborhood! project is a four-year multiphase community-based participatory action research strategy currently implemented in six public housing developments (n = 1009 households) across the province of Québec, Canada. The goal is to reduce the mental health disparities faced by these public housing tenants compared to the general population, while identifying which environmental and policy changes are needed to turn public housing settings into healthier environments. METHODS: The protocol involves three successive, interconnected phases: 1) Strengths and needs assessment, including community outreach and recruitment of tenants to collaborate as peer researchers, an exploratory qualitative component (photovoice), a systematic neighborhood observation, and a household survey; 2) Action plan development, including a community forum and interactive capacity-building and discussion sessions; 3) Action plan implementation and monitoring. The entire intervention is evaluated using a mixed-method design, framed within a multiple case study perspective. Throughout the project and particularly in the evaluation phase, data will be collected to record a) contextual factors (tenants' previous experience of participation, history of public housing development, etc.); b) activities that took place and elements from the action plan that were implemented; and c) short- and medium-term outcomes (objective and perceived improvements in the quality of the residential setting, both physically and in terms of mental health and social capital). DISCUSSION: The study will provide unprecedented evidence-based information on the key ingredients of a collective intervention process associated with the increased collective empowerment and positive mental health of public housing tenants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".