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Record W4409640229 · doi:10.1080/10530789.2025.2493396

Processes and experiences of women after leaving a shelter: a scoping review

2025· review· en· W4409640229 on OpenAlexafffund
Karla Jacobsen, Laurence Roy, Carrie Anne Marshall, Michel Perreault, Sally Richmond, Vanessa Seto, Beatriz Hoffmann-Kuhnt, Isabelle Boutemeur, Danielle Rouleau

Bibliographic record

VenueJournal of Social Distress and the Homeless · 2025
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsWestern UniversityDouglas Mental Health University InstituteMcGill University
FundersCatherine Donnelly Foundation
KeywordsPsychologyMedicine

Abstract

fetched live from OpenAlex

After a shelter stay, women frequently face continued housing and economic instability. This scoping review, which is a companion paper to our scoping review on outcomes for women post-shelter (Jacobsen et al. [2024]. Outcomes for women after leaving a shelter: A scoping review of the quantitative evidence. Women’s Studies International Forum, 105, 102921.), explores the experiences of women post-shelter stay, and factors that affect this transition. We followed the Levac et al. ([2010]. Scoping studies: advancing the methodology. Implementation Science, 5(1), 1–9.) framework for conducting scoping reviews. After screening 6,895 articles, 37 met the inclusion criteria. Four salient themes emerged relating to the experiences of women post-shelter: connection and community, finding a place to call home, creating a new life, and caring for self. Our findings add to the existing literature to underscore the paramount importance of ontological security and engagement in meaningful activities for women transitioning from shelter to housing. This review highlights the necessity of including the voices of women to understand what safety, security, and community integration mean to them. Including the voices of women with lived experience to guide research, practice and policy is imperative to find solutions that are socially just, accessible, trauma-informed, and gender-transformative.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.266
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.442
Teacher spread0.400 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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