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Record W4416926300 · doi:10.36939/cjur/vol28no1/art201

Verticality, Public Space and the Role of Resident Participation in Revitalizing Suburban High-rise Buildings

2019· article· W4416926300 on OpenAlexafffundvenueabout
Loren March, Ute Lehrer

Bibliographic record

VenueCanadian journal of urban research · 2019
Typearticle
Language
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsYork UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsRedevelopmentPublic spaceSpace (punctuation)Public policyRetrofittingUrban planningPoliticsUrban regeneration

Abstract

fetched live from OpenAlex

In this paper, we look at the role that public space may take on in the redevelopment of suburban high-risebuildings in the Greater Toronto and Hamilton Area (GTHA). We are interested in what role public space playsin the imaginary and how different forms of public participation in planning processes are beneficial to theoutcome of the redesign of high-rise buildings who are in need of repair and retrofitting due to their age andtheir social stigmatization. These suburban high-rises offer insight into newly proliferating forms of public space,and speak to the need for more diverse and specific physical, social and political articulations of public space.We find that by examining public space through the lens of verticality we are able to see how different planninginterventions, urban development processes, spatial contexts and competing imaginaries produce very differentand often hybrid forms. We base our findings upon selected planning and policy documents, media reports anddiscourse, and input from interviews with several locals involved in planning processes.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.015
Scholarly communication0.0060.003
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.048
GPT teacher head0.342
Teacher spread0.294 · 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

Citations3
Published2019
Admission routes4
Has abstractyes

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