Pathways of displacement: A pan-Canadian perspective on the nature and dynamics of rural and remote homelessness
Bibliographic record
Abstract
Homelessness is often described as a ‘wicked problem’. It is a complex, ill-defined and seemingly intractable public health crisis, crossing multiple sectors, with no immediate or easy fix. The issue of homelessness in Canada's rural and remote communities remains largely a hidden phenomenon receiving little attention from researchers, policymakers, and government officials. This oversight is alarming in light of the fact that the prevalence of homeless populations in rural and remote areas is significant, with rates equal to or higher than those of urban centres. The aim of this research is to address this knowledge gap by highlighting specific characteristics and contemporary trends of rural and remote homelessness. Understanding the nuances of this context is essential for developing targeted policies and interventions to prevent and reduce homelessness. Focus groups were held with service providers from ten distinct communities across Canada in 2021–2022, spanning five provinces and all three territories, and all falling within the Statistics Canada geographic classification of small population centres on the urban-rural continuum. From the focus groups, data on rural and remote homelessness were classified into the primary categories of who, help, where, and culture/context. Recent challenges, like COVID-19 and changes in the housing market, have significantly altered the conventional factors affecting homelessness in these settings. To decrease homelessness in these communities, a diverse approach is needed accounting for the social, structural, cultural, and contextual elements that influence rural and remote homelessness, instead of applying a blanket solution. • Rural and remote homelessness in Canada is widespread and growing. • Hidden homelessness and limited housing/social services in rural and remote Canada. • Displacement is driven by external factors such as COVID-19 and the housing market. • Homelessness is a consequence of structural and systems-level shortcomings. • Grassroots initiatives mobilize resources and break down stigma.
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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 | 0.000 | 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".