Competing perspectives on rural homelessness: Findings from a qualitative study in Ontario, Canada
Bibliographic record
Abstract
Rural homelessness in Canada has only recently been acknowledged, and several gaps remain in our understanding of the phenomenon and how it is influenced by the rural context. This qualitative exploratory study aimed to help understand the experience of housing insecurity, factors that lead to rural homelessness, and potential solutions to the housing crisis in a rural Ontario community. Interviews were conducted with 27 participants: 16 individuals who were housing insecure and 11 key informants who had knowledge of the local homelessness situation. Data collection took place between August 2020 and May 2021 and inductive analysis was concurrent. Findings revealed competing perspectives on the magnitude of the crisis, its root causes, and potential solutions to rural homelessness. The invisible nature of rural homelessness and values of individualism that assign responsibility for homelessness to poor choices rather than structural factors may account for these different perspectives. Stigma also played an important role in how homelessness was understood, particularly for individuals who were homeless and perceived to be using substances. The lack of privacy, limited services, and low housing stock in the rural environment contributed to challenges with overcoming homelessness. Strategies to help improve supports for individuals facing homelessness include anti-stigma education, capacity building, and inclusion of people with lived experience of homelessness in decision and policymaking. Prevention should also be incorporated into the response to rural homelessness through intersectoral collaboration and upstream policies that target the structural drivers of homelessness.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".