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Record W4255309770 · doi:10.32920/ryerson.14647668

The Myth of Master Planning: More than Urban Design: a Comparative Analysis of the Master-Planned Affordable Housing Developments Stuyvesant Town and Regent Park

2021· preprint· en· W4255309770 on OpenAlexaffabout
Tneshia Pages

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsRegentUrban planningMaster planAffordable housingEnvironmental planningPolicy analysisIdeologyPublic administrationSociologyPolitical scienceEconomic growthEngineeringCivil engineeringGeographyEconomicsLawPolitics

Abstract

fetched live from OpenAlex

This paper explores the role of urban planning policy, urban housing policy, and urban design on master planning. Though master planning as a concept has historically been tied to urban design, this paper argues that this notion is fundamentally flawed, and that urban planning policy and housing policy play an equally important role. This topic is explored through a case study analysis of Stuyvesant Town and Regent Park, master-planned affordable housing projects in New York City and Toronto, Ontario. With a focus on process, policy, and design, this paper will discuss how interpretations of master planning in New York and Toronto influenced the development of both housing projects. A comparative analysis of both projects highlights the multi-faceted nature of master planning, and demonstrate the importance of urban planning policy, housing policy, and urban design ideologies to master planning.

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)0.003
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.011
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0000.001
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 head0.132
GPT teacher head0.331
Teacher spread0.199 · 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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