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Record W7108228105 · doi:10.36939/cjur/vol24no2/art15

Streets Paved with Gold: Urban Expressway Building and Global City Formation in Montreal, Toronto and Vancouver

2016· article· W7108228105 on OpenAlexafffundvenueabout

Bibliographic record

VenueCanadian journal of urban research · 2016
Typearticle
Language
FieldSocial Sciences
TopicGlobal Urban Networks and Dynamics
Canadian institutionsSimon Fraser University
FundersSocial Sciences and Humanities Research Council of CanadaJohns Hopkins University
KeywordsGlobal cityMetropolitan areaGlobal networkGlobal SouthUrban planningUrban structure

Abstract

fetched live from OpenAlex

Montreal, Toronto and Vancouver are Canada’s most signifi cant locations of global city formation today. Their distinctive spatial development and mobility mix were greatly infl uenced by decisions regarding inner-city expressway building. This article explores the hypothesis that choices made regarding how to move motor vehicles through Canada’s three major metropolitan areas between 1960 and 1980 can be better understood by examining the dynamics of global city formation in these jurisdictions. Montreal implemented a comprehensive expressway network to align with its status as Canada’s leading global city during the 1960s. Toronto’s attempt to complete an expressway network was partial, reflecting fragmentary global city aspirations during the 1970s. Vancouver, where global city ambitions only began to form during the 1980s, cancelled urban expressway plans and became Canada’s ‘freeway-free’ major city. New insight into the structure of these cities can be gained when a global city analytical framework is applied to their urban expressway development experience.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.006
Scholarly communication0.0050.001
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 head0.027
GPT teacher head0.299
Teacher spread0.272 · 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 designNot applicable
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
Published2016
Admission routes4
Has abstractyes

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