Bibliographic record
Abstract
This study uses national survey and census data on shelter costs and income to describe changes in the proportion and the number of low‐income households spending more than half of their income on shelter. While affordability problems increased consistently over the last two decades for almost all classes of households, the problems are highly concentrated among those with low‐incomes. Women household maintainers are significantly more likely to experience problems and the number of income recipients in a household is a key indicator of a potential problem. While all regions and major cities had increasing problems, the data show major differences across regions and urban centres. No correlation is found between the growth of cities or the growth in rent levels and the growth of the proportion of low‐income households with severe affordability problems. Housing prices were remarkably stable during the 1990s and cannot be claimed as the main cause of the escalating problem. However, strong correlations relate the growth of affordability problems to city size and to the prevailing rent level, suggesting that land rent is a factor in determining the problem's spatial incidence and that continued concentration of the population in major cities will continue to fuel the growth of the problem. The most disturbing finding is that, for the most vulnerable groups, the prevalence and severity of affordability problems worsened during the 1990s, reflecting the consequences of a larger and longer trend toward increasing income inequality in Canadian society. The paper points to other research which links the affordability issue to homelessness and argues that the trends in affordability burdens be considered as ripe for serious policy intervention at all three levels of government. While specific policy conclusions cannot be based on this study, the results do point to the growing need for a change in Canadian housing policy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".