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Record W2342660116 · doi:10.1177/0042098015613207

Revitalisation gone wrong: Mixed-income public housing redevelopment in Toronto’s Don Mount Court

2015· article· en· W2342660116 on OpenAlexaboutno aff
Martine August

Bibliographic record

VenueUrban Studies · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsRedevelopmentPublic housingUrbanismNeighbourhood (mathematics)SociologyPublic administrationPolitical scienceLawArchitecture

Abstract

fetched live from OpenAlex

This article challenges the presumed benevolence of mixed-income public housing redevelopment, focusing on the first socially-mixed remake of public housing in Canada, at Toronto’s Don Mount Court (now called ‘Rivertowne’). Between 2002 and 2012 the community was demolished and replaced with a re-designed ‘New Urbanist’ landscape, including replacement of public housing (232 units) and 187 new condominium townhouses. While mixed redevelopment is premised on the hope that tenants will benefit from improved design and mixed-income interactions, this research finds that many residents were less satisfied with the quality of their housing, neighbourhood design, and social community post-redevelopment. Drawing on in-depth qualitative interviews and ethnographic participant observation, this article finds that tenant interviewees missed their older, more spacious homes in the former Don Mount, and were upset to find that positive community bonds were dismantled by relocation and redevelopment. Challenging the ‘myth of the benevolent middle class’ at the heart of social mix policy, many residents reported charged social relations in the new Rivertowne. In addition, the neo-traditional redesign of the community – intended to promote safety and inclusivity – had paradoxical impacts. Many tenants felt less safe than in their modernist-style public housing, and the mutual surveillance enabled by New Urbanist redesign fostered tense community relations. These findings serve as a strong caution for cities and public housing authorities considering mixed redevelopment, and call into question the wisdom of funding welfare state provisions with profits from real estate development.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.095
GPT teacher head0.269
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations35
Published2015
Admission routes1
Has abstractyes

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