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Record W2728503385 · doi:10.7202/1050578ar

The Transit-Oriented Development Model in Montreal (Canada): Mobilizing a Concept and Negotiating Urban Development at the Local and Metropolitan Scale

2017· article· en· W2728503385 on OpenAlexaffvenueabout
Maude Cournoyer-Gendron

Bibliographic record

VenueEnvironnement urbain · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversité du Québec à MontréalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMetropolitan areaNegotiationRegional scienceScale (ratio)Transit (satellite)Urban planningEconomic geographyGeographyPolitical scienceTransport engineeringSociologyEnvironmental planningEconomic growthPublic transportEngineeringCivil engineeringSocial scienceCartographyEconomics

Abstract

fetched live from OpenAlex

The concept of transit-oriented development (TOD) has now become a fixture in planning documents of metropolitan areas around the world. Looking at the Greater Montreal area, this article discuss the recontextualisation of the (abstract) idea of TOD and the specific ways in which it has been defined, implemented and used by local and metropolitan actors. Set up into a centerpiece of the dominant discourse in metropolitan planning, the TOD also serves as a mean of negotiation and legitimization for local elected officials in a context of multi-layered governance.

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: none
Teacher disagreement score0.111
Threshold uncertainty score0.803

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 studies0.0140.010
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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

Citations2
Published2017
Admission routes3
Has abstractyes

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