Experiences of belonging following homelessness: a systematic review and meta-aggregation
Bibliographic record
Abstract
Belonging is a human need and an essential component of community integration following homelessness. Little is known about the range of studies exploring experiences of belonging following homelessness. We conducted this systematic review and meta-aggregation to address this gap using Joanna Briggs Institute (JBI) methodology following Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines (PRISMA). We searched seven databases (EMBASE; PsychINFO; CINAHL; Medline; AMED; Nursing and Allied Health Database; and Sociological Abstracts), combining three main concepts: 1) homelessness; 2) belonging; and 3) transition. The search identified 2504 titles and abstracts. Of these, we included 33 studies in our review and meta-aggregation. Our meta-aggregation generated four themes describing experiences of belonging following homelessness: 1) developing a sense of belonging is a challenging process in the transition to housing; 2) shifting connections and finding new belonging; 3) belonging through engaging in meaningful activities; and 4) housing as a foundation for connection. These findings indicate that housing stability creates opportunities to belong but developing a sense of belonging is a difficult process involving changes in social networks facilitated by engaging with others in meaningful activities.
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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 | 0.035 | 0.105 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.021 |
| Bibliometrics | 0.020 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 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".