Public housing tenants’ perspective on residential environment and positive well-being: An empowerment-based <i>Photovoice</i> study and its implications for social work
Bibliographic record
Abstract
Summary Although tenants of public housing face numerous challenges, recent research suggests they can experience positive well-being. The study examines a group of tenants’ perspective on structures of their residential environment that influence their positive well-being, using the empowerment-based Photovoice method. Ten peer-researchers took pictures, participated in facilitated group discussions, and performed a thematic analysis. The study presents themes emerging from the pictures, as well as concrete outcomes of implementing such a method in a public housing setting. Findings Six themes emerged from the pictures taken: (1) a pleasant home, inspiring pride; (2) variety of local resources; (3) mutual support and social participation; (4) control over life situations; (5) social, leisure and growth opportunities; (6) beneficial access to nature. The findings reveal the nuances of tenants’ relationships with their residential environment, which has the potential to support their emotional, psychological, and social well-being. However, several needs for improvement were also identified, as well as avenues for tenants to take more power over these negative situations. The Photovoice method appears to have produced positive outcomes in terms of environmental improvement and tenant empowerment. Applications The study suggests social workers should bear in mind the multifaceted person–environment relationship of the people they work with. It also emphasizes that public housing tenants can play an active role in making their environment a place where they can flourish. The Photovoice method is highlighted as a useful tool for social work community practitioners to support tenant empowerment.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".