(Em)placing recovery: Sites of health and wellness for individuals with serious mental illness in supported housing
Bibliographic record
Abstract
This study used photo-elicitation methodology to explore how the move from supervised to supported housing affects recovery and community connections for individuals living with serious mental illness (SMI) in four Canadian cities. Qualitative interviews conducted in 2015 revealed five themes: (1) the characteristics distinguishing home from housing; (2) the importance of amenities offered by supported housing; (3) the connections between accessibility, mobility, and wellbeing; (4) the role of certain places in facilitating aspects of recovery such as offering hope or facilitating social connectedness; and (5) the concrete and metaphorical impact of changing vantage points on identity (re)construction. Utilizing therapeutic landscapes as an analytical framework, and combining insights from the health geography, and mental health (MH) housing and recovery literatures, this study deepens current understanding of how everyday places-conceptualized as therapeutic landscapes-directly and indirectly support MH recovery for individuals with SMI. Implications for research on housing, and on the spatial aspects of recovery processes are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".