Identification of Housing Stabilization Models for Youth Exiting Homelessness: A grey literature review
Bibliographic record
Abstract
This systematic review describes the international grey literature addressing housing stabilization support models for youth. The review yielded 15 reports with a range of information on preventative activities that focus on well-being embedded within the various form of housing stabilization. These approaches build on the premise that housing alone does not provide an effective solution to youth homelessness. Analyses of the content of these reports revealed both cross-cutting, process-oriented themes, alongside descriptions of the outcomes associated with specific intervention models. These findings emphasized the importance of intersectoral collaboration, early intervention coupled with intensive case management, and applying an attachment-oriented theoretical framework in guiding model implementation. Other highlighted results include specific models of housing stabilization with a particular concentration on housing intervention programs that address the interdependency between housing, income, and education. These stabilization supports, practices, and policies offered by organizations were associated with improved outcomes. This review, however, was limited by a lack of controlled studies amongst the reports and, in many instances, a lack of clarity regarding the service models delivered. Despite these limitations, this review provides an overall view of the grey literature evidence regarding the strategies to support young people in transition out of homelessness that complements and expands upon the academic literature in this area. Further research is needed with clearer and more rigorous methods, more detailed intervention descriptions, as well as data on applicability for visible minorities and specific employment interventions tied with housing supports.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".