MétaCan
Menu
Back to cohort
Record W4243571488 · doi:10.32920/ryerson.14665026

Building Community: a Critical Appraisal of Toronto’s Tower Renewal Program

2021· preprint· en· W4243571488 on OpenAlexaffabout
Filip Filipović

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRedevelopmentTowerRealmPlacemakingPolitical sciencePhenomenonPerformative utteranceSociologyPublic administrationEnvironmental planningPublic relationsEngineeringCivil engineeringArchitectural engineeringUrban planningGeographyUrban designLaw

Abstract

fetched live from OpenAlex

High-rise housing is a global phenomenon. In Toronto, the sheer number of tower blocks and declining conditions within them has pointed to the importance of redeveloping high-rises in order to improve their current performative capacity and secure their use for future generations. In addition, improving the public realm and social infrastructure in these communities has emerged as an important component of the redevelopment approach. Looking at the City of Toronto’s Tower Renewal program, the paper critically evaluates its environmental, economic and social/cultural objectives using Tower Renewal documents, local case studies and relevant literature. Analysis of program specifics leads to a greater understanding of the potential and prospects, as well as areas for improvement in tower redevelopment programs, the roles and collaborative relationships between participating parties, and how placemaking processes are and can be pursued and accommodated in redevelopment programs.

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)0.013
metaresearch head score (Gemma)0.019
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 score0.187
Threshold uncertainty score0.959

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0200.011
Scholarly communication0.0090.003
Open science0.0030.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.317
Teacher spread0.303 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same topicUnderground infrastructure and sustainabilityFrench-language works237,207