Residential segregation and inequality: Considering barriers to choice in Toronto
Bibliographic record
Abstract
Abstract Segregation of visible minorities has persisted throughout time in Toronto. In examining these concentrations, the literature has been heavily focused on the notion that visible minorities are choosing to live in proximity to their respective ethno‐racial groups and that these are spaces of aspiration rather than marginalization in Canada. This paper raises questions about the assertion of “self‐segregation” by emphasizing affordability constraints on residential choices that are often rooted in discrimination in the labour market. Census data from 2016 and an adopted neighbourhood classification scheme were used to understand the spatial patterning of visible minorities in the Toronto census metropolitan area and highlight differences in the socio‐economic characteristics of visible minority dominant and white dominant census tracts. The findings invite the inference that economic opportunities play a critical role in the residential choices of visible minorities and raise concerns about the quality of life in visible minority neighbourhoods. This research contributes to our understanding of how social inequalities have impacted the socio‐spatial organization of the city of Toronto .
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".