Belonging through meaningful activity in the transition from unhoused to housed
Bibliographic record
Abstract
BACKGROUND: Belonging is closely associated with well-being, yet individuals with experiences of being unhoused are likely to experience social exclusion and challenges with developing a sense of belonging. Engagement in meaningful activity has been linked to belonging; however, there are no focused studies exploring experiences of how engaging in meaningful activities influences belonging. Meaningful activities are things we do that bring value to our lives. PURPOSE: To explore how engaging in meaningful activities may influence experiences of belonging following homelessness through a secondary analysis of qualitative interviews. METHOD: Using interviews conducted in a community-based participatory action study exploring the transition to housing following homelessness (n = 19), we conducted a thematic analysis using the method described by Braun and Clarke. Participants were recruited through communication with local organizations supporting individuals with lived and living experiences of being unhoused as well as through presentations at drop-in organizations. An intentional effort was made to recruit diverse participants regarding housing status, age, and gender. Inductive analysis was used to conduct initial coding, focusing on belonging and engaging in meaningful activities. We then analyzed the codes abductively, using Bourdieu's Social Capital Theory to inform this analysis. FINDINGS: The overarching essence generated in our analysis was: "I don't feel like I belong…everything in the world is not for me…it's for people with…enough money to…enjoy those things". Within this overall essence, we generated three themes: 1) Human connection: "being where I am with people who care about me, I actually feel good"; 2) Social exclusion: being a "regular member of society"; and 3) Non-human connection: "my cats…are like my kids to me." Participants described numerous contextual factors that challenged them as they sought belonging following homelessness, including financial limitations and other societal factors. CONCLUSION: Our findings suggest that meaningful activity was an important pathway to belonging for participants in this study.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".