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Record W2002269567 · doi:10.1068/a42519

Displacing New York

2010· article· en· W2002269567 on OpenAlexaff
Elvin Wyly, Kathe Newman, Alex Schafran, Elizabeth Lee

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGentrificationCapitalizationAsset (computer security)RestructuringDisplacement (psychology)Value (mathematics)EconomicsInterpretation (philosophy)WelfareWelfare statePublic housingPublic economicsPolitical scienceMarket economyEconomic growthLawFinance

Abstract

fetched live from OpenAlex

The capitalization of urban property markets intensifies the contradictions between housing as use-value affordability versus exchange-value asset accumulation, and exacerbates displacement pressures. Policies designed to deal with these contradictions—public housing and rent regulations—allow some low-income renters to resist displacement, particularly in gentrifying neighborhoods. Unfortunately, the resulting empirical configuration has been interpreted in ways that cast doubt on the extent of displacement, its causal links to gentrification, and the necessity of protective policies. In this paper we present an alternative interpretation, using New York City as a case study to analyze the spatial evolution of displacement pressures amidst the restructuring of an embattled yet vital municipal welfare state.

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)0.000
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 score0.370
Threshold uncertainty score0.736

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0230.001

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 head0.023
GPT teacher head0.238
Teacher spread0.215 · 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

Citations82
Published2010
Admission routes1
Has abstractyes

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