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Record W2066982704 · doi:10.1177/1078087410393472

Retail Gentrification and Race: The Case of Alberta Street in Portland, Oregon

2011· article· en· W2066982704 on OpenAlexaboutno aff
Daniel Monroe Sullivan, Samuel Shaw

Bibliographic record

VenueUrban Affairs Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsGentrificationMainstreamWhite (mutation)Race (biology)Diversity (politics)Creative classSociologyGender studiesGeographyPolitical scienceEconomic growthLawAnthropology

Abstract

fetched live from OpenAlex

Alberta Street is emblematic of Portland’s image as a city that embraces the “creative class,” ranking high in being “bohemian” and embracing “diversity.” It is a street that has had a decline in Black businesses and an increase in White ones, both mainstream and bohemian. Through interviews with longtime Black and White residents, we find that race is salient for understanding their use and opinion of the new retail sector. Many Blacks have negative feelings, and they use racial language to articulate why they dislike the products offered and how they feel culturally excluded. Longtime, mainstream White residents, in contrast, fully embrace the new retail. These findings should give pause to cities that promote economic development by making themselves attractive to the “creative class”: They may be refashioning their cities and neighborhoods—including their retail—in a way that is hostile to some forms of diversity, including longtime Black residents in gentrifying neighborhoods.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.671

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 studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.284
Teacher spread0.217 · 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 designObservational
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

Citations154
Published2011
Admission routes1
Has abstractyes

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