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Record W3136036163 · doi:10.1080/02723638.2020.1832376

Gentrification in large Canadian cities: tenure, age, and exclusionary displacement 1991-2011

2021· article· en· W3136036163 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUrban Geography · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGentrificationMetropolitan areaRentingStock (firearms)Housing tenureDemographic economicsLabour economicsEconomicsGeographyEconomic growthPolitical science

Abstract

fetched live from OpenAlex

This paper contributes to the gentrification literature by asking how tenure changes, housing stock changes, and generational shifts might be related to gentrification as identified by household income growth in the inner cities of Canada’s three largest metropolitan areas. We use a modified shift-share analysis of changes in tenure, housing stock, and age-tenure cohorts between 1991 and 2011 to examine these questions in Toronto, Montreal, and Vancouver, Canada’s largest metropolitan areas. We find that in each case, gentrification is associated with an absolute decline in non-condo private-sector rental units, and that construction of non-market/social housing units has not been sufficient to compensate for the private-sector units lost to gentrification. Our analysis demonstrates that changes in the class structure of households, more than generational or age-cohort composition shifts, are at the heart of inner-city transformations in tenure and income among households. The big story is the absolute loss of affordable rental units in each inner city, and the concomitant exclusionary displacement of lower-income households that has resulted.

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)0.000
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 score0.450
Threshold uncertainty score0.905

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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