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Record W2145834515 · doi:10.1177/0042098008097103

Are There Limits to Gentrification? The Contexts of Impeded Gentrification in Vancouver

2008· article· en· W2145834515 on OpenAlexaffabout
David Ley, Cory Gregory Dobson

Bibliographic record

VenueUrban Studies · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGentrificationNeighbourhood (mathematics)DowntownPoliticsEconomic geographyPopulationSociologyGeographyEconomic growthPolitical scienceEconomicsDemographyLawArchaeology

Abstract

fetched live from OpenAlex

This paper examines conditions that impede inner-city gentrification. Several factors emerge from review of a scattered literature, including the role of public policy, neighbourhood political mobilisation and various combinations of population and land use characteristics that are normally unattractive to gentrifiers. In a first phase of analysis, some of these expectations are tested with census tract attributes against the map of gentrification in the City of Vancouver from 1971 to 2001. More detailed qualitative field work in the Downtown Eastside and Grandview-Woodland, two inner-city neighbourhoods with unexpectedly low indicators of gentrification, provides a fuller interpretation and reveals the intersection of local poverty cultures, industrial land use, neighbourhood political mobilisation and public policy, especially the policy of social housing provision, in blocking or stalling gentrification.

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)0.002
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.599

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0120.012
Scholarly communication0.0090.002
Open science0.0010.010
Research integrity0.0010.002
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 head0.079
GPT teacher head0.327
Teacher spread0.248 · 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

Citations160
Published2008
Admission routes2
Has abstractyes

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