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Record W4232961238 · doi:10.32920/ryerson.14655435

Visions of a polycentric suburb : the evolution of car-centric design

2021· preprint· en· W4232961238 on OpenAlexaboutno aff
Mark Siemicki

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsVisionUrban sprawlPoliticsOrder (exchange)DreamNew UrbanismArchitectural engineeringPolitical scienceSociologyEconomic geographyUrban planningBusinessEngineeringCivil engineeringGeographyLaw

Abstract

fetched live from OpenAlex

The following thesis investigates emerging issues surrounding car-centric design know as urban sprawl and questions whether or not it is feasible and appropriate for cities to continue sprawling in a car-centric manner given changing conditions. Social, political, environmental and economical concerns have surfaced putting a damper on the once great "American Dream" raising concerns that car-centric design can prove detrimental to humanity. The roots of modernist design are discussed and the ideas behind modernists' intentions analyzed while juxtaposing modernist vision to the real outcomes of modernism. Modernist ideas are compared and contrasted to new and old theories that challenge the modernist ideals in order to propose a new direction for future urban development. The design project takes into account the importance of connection and network through infrastructure in a globalized world. Transit infrastructure (high speed rail, improved commuter rail, rapid transit and light rail) is proposed on a number of scales in the Southern Ontario region to act as a catalyst for responsible growth interconnecting future intensified polycentric suburban cities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.208
Teacher spread0.185 · 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 teacher head, 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 routes1
Has abstractyes

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