Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Explanations of urban segregation by income must look to the housing system, alongside local factors. In welfare capitalist countries, the respective roles of private and social rental cannot be assumed. This study draws on policy literature as well as census and administrative data to explain how a shifting housing policy and market regime shaped the evolving segregation of low-income renters in Greater Toronto, 1971-2006. A huge postwar private-rental apartment building sector, and greatly expanding social housing, almost equally shaped this geography. The postwar regime created a ‘mixed economy of rental’, mixed-income suburbs, and two decades of sustained central-city mix despite gentrification. Social housing at 10-12 percent of total housing production—departing from long-run trends in liberal-welfare Canada—absorbed half of low-income demand, with large mitigating impacts on neighbourhood change. After 1980, neoliberal trends of declining rental incomes and production directly fed more segregation, inner-suburban ‘decline’, and less-mixed outer suburbs. Spatial patterns arose from distinctive national and local influences as well as reflecting international trends. The study confirms the significance of metropolitan growth in small-area trends, and of dispersed rental production in spatial income mix. The findings have relevance internationally in contexts of mixed social and private rental systems and surging ‘built-to-let’ production.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it