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Record W4415936396 · doi:10.1080/26884674.2025.2573927

Warriors of Shaolin: Hip hop and racialized spatial order in Staten Island

2025· article· en· W4415936396 on OpenAlex
Tyeshia Redden

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.

Bibliographic record

VenueJournal of Race Ethnicity and the City · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American and Latino Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOrder (exchange)NarrativeRace (biology)EthnographyField (mathematics)

Abstract

fetched live from OpenAlex

Following the announcement of the Verrazzano-Narrows Bridge in 1940s New York City, the overwhelmingly (ethnic) White populace of Staten Island feared that Black Americans were soon to follow. Numerous neighborhood organizations lobbied for more restrictive zoning policies that isolated Black communities, particularly multiple-dwelling buildings and public housing developments. The resulting policies expanded a spatial order and entrenched “negative space,” racialized geographic boundaries that emphasized the Whiteness of some neighborhoods against the Blackness of others. Lever aging the narrative accounts and cultural production of Staten Island’s most famous export, the hip hop group Wu-Tang Clan, I offer an intimate portrait of anti-Black racism and structural violence that presents the Wu-Tang Clan as literal and metaphorical fugitives leveraging hip hop to reclaim their urban narratives. I conclude that despite decades of anti-Black racism and exclusionary zoning creating a vicious and self-perpetuating cycle that encourages racial violence, Wu-Tang Clan “ain’t nothing to f*** wit.”

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)0.002
metaresearch head score (Gemma)0.001
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 score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.328
Teacher spread0.310 · 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