Bibliographic record
Abstract
House prices have increased significantly in Canada over the past decade, driving household debt and residential construction activity to historical highs. Although macro-prudential tightening has slowed the pace of household borrowing in the last few years, house prices have continued to trend higher, and affordability remains a major challenge in urban centres. First-time home buyers must therefore spend more of their incomes to purchase a house and are vulnerable to future interest rate hikes. Overbuilding in the condominium sectors of some cities appears to be a source of risk, especially if a major price correction in these segments spills over into other markets. The country benefits from a sound and effective housing finance system, which performed well throughout the global financial crisis thanks to strong regulatory oversight and explicit government backing of the mortgage market. Nonetheless, the dominance of the crown corporation CMHC in the mortgage insurance market concentrates a significant amount of risk in public finances. Improving competitive conditions in the mortgage insurance market could help diversify these risks and reduce taxpayer contingent liabilities, while introducing coverage limits on loan losses would better align private and social interests. There may be a shortage of rental housing in several cities, especially in the range that low-income households can afford. Urban planning policies have resulted in low-density residential development which contributes to relatively high transport-related carbon emissions. Addressing these externalities requires stronger pricing signals for land development, road use, congestion and parking, combined with better integration of public transit planning. To prevent the marginalisation of low-income households, planning policies should support social mix and increase incentives for private-sector development of affordable housing. This Working Paper relates to the 2014 OECD Economic Review of Canada (www.oecd.org/eco/surveys/Canada).
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".