The two Torontos: Young people navigating the core-inner suburb socio-spatial divide
Bibliographic record
Abstract
In 2014 Toronto was named ‘Youthful City of the Year’ by the global Youthful Cities initiative. The ranking was supposed to be indicative of Toronto’s progressiveness and as a place where youth are equipped to thrive. Toronto also ranked number one for diversity. Much of Toronto’s celebrated diversity exists in the inner suburbs of the city. The homogenous framing of Toronto as captured by the Youthful Cities initiative neglects the lived realities of young people who live on the fringes of the city. This is heightened in a context of increasing socio-economic inequalities that is spatially concentrated. In this paper I examine how divergences in the city are spatially produced and navigated by young people that live both symbolically and geographically on the fringes. I argue that Toronto is differentiated along lines of race and socio-economic status that is reified through the socio-spatial division between the core of the city and the inner suburbs.
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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 | 0.026 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.024 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".