Motels as rural homeless shelters: A qualitative study across five Ontario communities
Bibliographic record
Abstract
Objectives Rural homelessness is increasing, yet there is limited infrastructure to intervene in rural communities. During COVID-19, additional funding helped repurpose motels as shelters, and some of these motel-based shelters continue today. The objectives of this study were to understand the experience of living in a rural motel, whether motels are a viable shelter option for rural communities, and strategies for their success. Method s: Interpretive description was used to guide qualitative interviews with 27 individuals who used or administered motels as rural homeless shelters across five communities in rural Ontario. On-site observations in two settings helped triangulate data and immersed the lead researcher in the regional context. Results Participants with lived experience (N=16) described many challenges living in a motel room yet were grateful for a secure and private space. Some participants felt happier, healthier, and their substance use decreased, although they also noted limited autonomy. Participants administering motel programs (N=11) appreciated the opportunity to strengthen connections with clients and community partners yet struggled to prevent overdoses and motel damage. Staff worked hard to maintain relationships with motel owners and get ahead of problems, suggesting layout, 24/7 presence, and integrated services were important for program success. Longer-term programs offered more stability, feelings of belonging, and avoided the stress of not knowing when one might be asked to leave. Conclusions : Rural motel shelters offered an innovative response to unsheltered homelessness, demonstrating existing rural infrastructure can be repurposed as emergency shelter, transitional housing, or supportive housing with adequate supports.
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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 | 0.001 | 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 | 0.001 |
| 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".