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Record W2143611118 · doi:10.1111/1467-9663.00276

Planning, policy and polarisation in Vancouver's downtown eastside

2003· article· en· W2143611118 on OpenAlexfundaboutno aff
Heather A. Smith

Bibliographic record

VenueTijdschrift voor Economische en Sociale Geografie · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaAmerican Association of Geographers
KeywordsDowntownNeighbourhood (mathematics)Urban policyDisadvantageFutures contractUnintended consequencesUrban planningPolitical scienceEconomic geographySociologyGeographyEconomic growthEconomicsCivil engineering

Abstract

fetched live from OpenAlex

ABSTRACT Widely known as Vancouver's ‘skid road’ the Downtown Eastside struggles with the pressures of socio‐spatial polarisation. While the neighbourhood has experienced deepening poverty, widening disadvantage, the entrenchment of an open air drug market, epidemic levels of HIV/AIDS and rising crime rates, it has also undergone extensive residential and commercial revitalisation. This paper explores, qualitatively, the City of Vancouver's policy and planning role in the spatial and temporal collision of both upgrading and downgrading within this single urban neighbourhood. Particular attention is paid to the unintended geographic and social impacts of municipal policy and the challenges faced by the city in attempting to address the conflicting expectations of community interests and the possibility of diametrically opposed, yet equally possible, neigh‐bourhood futures. The paper points to the necessity of continued research on the local dynamics, policy implications and scale of intra‐urban socio‐spatial polarisation.

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)0.001
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: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.004
Scholarly communication0.0060.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.282
Teacher spread0.270 · 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

Citations51
Published2003
Admission routes2
Has abstractyes

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