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Record W4383105922 · doi:10.3389/frsc.2023.1196428

From “smart growth” to “frontier” intensification: density, YIMBYism, and the development of garden suites in Toronto

2023· article· en· W4383105922 on OpenAlexaffabout
Susannah Bunce

Bibliographic record

VenueFrontiers in Sustainable Cities · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsFrontierSmart growthPoliticsSustainable developmentNarrativeUrbanismNew UrbanismIntervention (counseling)Political scienceEconomic growthSociologyEconomic geographyUrban planningGeographyEconomicsArchitectureEngineeringCivil engineeringArchaeologyArtLaw

Abstract

fetched live from OpenAlex

Toronto's official intensification policy has directed increased density primarily through residential development over the last 20 years. Recently, new intensification efforts have focused on increasing density in existing residential neighborhoods through so-called “gentle density” and “missing middle” built form, as a new “frontier” of intensification. These efforts have included a focus on the production of garden suites on residential properties. In this short intervention, I suggest that Yes-In-My-Backyard narratives, that celebrate intensification, raise problematic arguments under the guise of sustainable urbanism and liberal progressive politics which foreclose important critiques of intensification. I argue that increased YIMBYism and new intensification efforts in Toronto are entwined with homeownership wealth-building and market-oriented property 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.533

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.008
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2023
Admission routes2
Has abstractyes

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