The role and meaning of interim housing in housing first programs for people experiencing homelessness and mental illness.
Bibliographic record
Abstract
The housing first (HF) model for individuals experiencing homelessness and mental illness differs by design from traditional models that require consumers to achieve "housing readiness" by meeting program or treatment prerequisites in transitional housing settings prior to permanent housing placement. Given a growing body of evidence for its favorable outcomes and cost effectiveness, HF is increasingly seen as an alternative to and argument against these traditional programs. As such, it is important that the elements and implementation challenges of the HF model be clearly understood and articulated. This qualitative study explored a largely unexamined aspect of the HF model-the need for and meaning of temporary residential settings (interim housing), a place to stay while waiting to secure permanent housing-using interviews and focus groups with service providers and consumers who experienced interim housing during implementation of HF in a large urban center. Although interim housing may not be necessary for all programs implementing the model, our study revealed numerous reasons and demands for safe, flexible interim housing options, and illustrated how they influence the effectiveness of consumer recovery, continuous service engagement, and 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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".