The Politics of Place: Place‐making versus Densification in Toronto's Tower Neighbourhoods
Bibliographic record
Abstract
Abstract Toronto's Tower Neighbourhood Renewal (TR) programme is a municipal government initiative tackling aging high‐rise apartment building clusters in need of physical upgrades. One strategy for a more vibrant future for those clusters is densification or new infill housing. The main argument of the essay is that the unique urban structure of Toronto's inner suburbs challenges the implementation of TR's densification strategy. The proximity of many residents occupying privately owned single‐family homes close to the tower neighbourhoods has implications for the governance of TR in Toronto. Having created place‐frames firmly linked to their own identities as single‐family homeowners, these residents reject an encroachment of the ‘urban' (through higher residential densities) and of the ‘Other' (through a potential increase in low‐income, immigrant and visible minority tower renters). A 2011 design charrette in the Toronto neighbourhood of Weston serves as a case study, exemplifying the tensions between neighbourhood resident place‐frames and the goals of the TR project. This essay is based on an analysis of public policy documents and public participation reports, as well as notes from direct observation during the Weston 2021 Design Charrette.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".