Qualitative findings from a Housing First evaluation project for homeless Veterans in Canada
Bibliographic record
Abstract
LAY SUMMARY This two-year study implemented a Housing First approach among homelessness services for Veterans in four cities across Canada (Victoria, Calgary, London, and Toronto). This approach included peer support and harm reduction resources for Veterans. To obtain a detailed evaluation of personal experiences and opinions, focus groups were held with Veterans, housing staff, and stakeholders at three time points during the study: July-September 2012, May-June 2013, and January 2014. Harm reduction and peer support were regarded as positive aspects of this new approach to housing and homelessness. It was suggested that greater mental health support, support from peers with military experience, and issues regarding roommates should be considered in future implementations of housing services for Veterans. It was also noted that to support personal stabilization, permanent housing is preferred over transitional or temporary housing. Future housing programs serving Veterans experiencing homelessness should consider the addition of harm reduction and peer support to further enhance services and help maintain housing stability.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".