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Record W2020385208 · doi:10.1177/0042098014524287

Urban rapid rail transit and gentrification in Canadian urban centres: A survival analysis approach

2014· article· en· W2020385208 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUrban Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsGentrificationCensusEconomic geographyUrban rail transitRail transitRegional scienceUrban transitTransit (satellite)Transport engineeringGeographyPublic transportEconomic growthSociologyEconomicsDemographyEngineeringPopulation

Abstract

fetched live from OpenAlex

Despite the existing knowledge that urban rapid rail transit has many effects on surrounding areas, and despite some attempts to understand the links between transit and gentrification, there remain methodological gaps in the research. This study addresses the relationship between the implementation of urban rapid rail transit and gentrification, which is conceived of as an event. As such, an event analysis approach using ‘survival analysis’ is adopted as the statistical analytical tool. It tests whether proximity to rail transit is related to the onset of gentrification in census tracts in Canada’s largest cities. It is found that proximity to rail transit, and to other gentrifying census tracts, have a statistically significant effect on gentrification in two of the three cities analysed. By providing a methodological framework for the empirical analysis of the impact of urban rail transit on gentrification, this paper is a reference for both researchers and transportation planners.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.273
Teacher spread0.240 · 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