Local Conditions and the Prevalence of Homelessness in Canada
Bibliographic record
Abstract
In 2018, the federal government coordinated point-in-time counts in 61 Canadian communities. These counts, all conducted over the course of a few nights during the months of March and April, revealed that 25,216 people were experiencing homelessness. Of those, 20,803 slept in emergency shelters while 4,481 slept on the streets, in cars, or in some other unsuitable place. Reviewing the data for 49 of those 61 communities, this paper examines the impact of community-level conditions on the prevalence of homelessness. The structural determinants of both sheltered and unsheltered homelessness are examined. The analysis shows that more expensive low-quality rental units have a strong positive relationship with the numbers of people staying in homeless shelters. A higher percentage of people in a community living in poverty is also related to increased numbers of people having to make use of homeless shelters. Increases in social assistance income, which undoubtedly improved the well-being of recipients, had no significant relationship with the number of people experiencing homelessness. This latter result is consistent with individuals and families with low income having a small income elasticity of housing demand. For these individuals and families, marginal additions to income are first used to relieve constraints on their budgets for food, utilities, and other necessities rather than being used to finance improvements in housing conditions. The fraction of the population that self-identifies as Indigenous is positively related to both sheltered and unsheltered homelessness, a result consistent with claims of discrimination in housing markets. Finally, a milder climate is associated with higher numbers of people experiencing unsheltered homelessness. These results suggest the most effective policy response to addressing homelessness is to lower the cost of shelter, an outcome best achieved by increasing the supplyof shelter that can be afforded by individuals and families with limited income. Tothis end, public policies directed toward reducing the cost of construction, policiesthat include reviewing density restrictions and land-use regulations and offering tax incentives, can be effective. Preventing the disappearance of single-room occupancy hotels, boarding houses, trailer parks and other forms of housing affordable to people with limited income are other policy responses likely to be associated with decreasesin homelessness. Increasing the stock of government-owned housing is another policy option, one best suited for providing housing for people whose homelessness is caused or exacerbated by disability, mental illness, substance abuse or other health issues requiring other support services. Marginal increases in income support, while important for increasing the well-being of individuals and families with limited income, are unlikely to be associated with decreases in homelessness unless they are sufficiently large to significantly reduce rates of poverty in the community.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".