Examining second-stage shelters: insights into housing instability and tailored support for IPV survivors
Bibliographic record
Abstract
BACKGROUND: Intimate Partner Violence (IPV) exposes women and children to a wide range of challenges across housing, employment, social connections, and child well-being and is a public health issue. IPV survivors are at heightened risk of housing insecurity and homelessness. Emergency shelters have historically offered respite and support, but the emergence of second-stage shelters provides longer-term solutions. Despite their significance, there has been a lack of comprehensive research on second-stage shelters. This study focuses on understanding the needs of IPV survivors accessing second-stage shelters, aiming to illuminate unexplored aspects of support. To examine the current published peer-reviewed literature and gray literature on second-stage shelters, a scoping review was conducted. METHODS: This scoping review used the method suggested by Arksey & O'Malley (2005) and considered all studies that focused on women who had experienced IPV and were accessing transitional housing/second-stage shelters. RESULTS: Sixteen articles, mainly from the USA and published between 1985 and 2022, were included in the analysis. The findings highlighted themes of (1) a safe(r) place, with the subtheme of 'gated' communities, and (2) programming and services, with the subtheme of does one size fit all? and (3) insider support, with subthemes of paid insider support and peer insider support. CONCLUSIONS: Housing instability was evident, and the need for multiple and individualized tailored options of programming and support along with housing security was identified. Second-stage housing policy and practice implications are addressed which illuminate unexplored aspects of support.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".