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Record W4237742539 · doi:10.32920/ryerson.14668299

Lebreton Flats : Redeveloping Former Brownfield Land in Canada's Capital. A Study of Urban Design Qualities and Best Practices

2021· preprint· en· W4237742539 on OpenAlexaffabout
Sophia Kanavas

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsToronto Metropolitan UniversityNational Capital Commission
Fundersnot available
KeywordsBrownfieldCapital regionUrban designCommissionRealmEnvironmental planningCapital (architecture)Urban planningPublic spaceNational capitalCivil engineeringBusinessRegional scienceGeographyRedevelopmentArchitectural engineeringEngineeringArchaeology

Abstract

fetched live from OpenAlex

In 2014, the National Capital Commission made a call for proposals to develop approximately 9.3 hectares of Le- Breton Flats, a former brownfield in Canada’s Capital. The objective is to create a new mixed-use community characterized by an institutional use to anchor the development. This report seeks to investigate what policies and urban design principles may be used to develop LeBreton Flats through a review of brownfield and urban design literature; policy analysis; and a review of case precedents for brownfield redevelopments. The recommendations provided seek to establish that good urban design for LeBreton Flats must contain elements of mixed-land uses with compact design; an institutional use of international or national significance to attract visitors and support local residents; walkable neighbourhoods with integrated public transportation; public realm dedication through parks and open space access to the waterfront; and innovative, architectural building construction with green design standards.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.138
GPT teacher head0.345
Teacher spread0.207 · 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 designQualitative
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

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