Warriors of Shaolin: Hip hop and racialized spatial order in Staten Island
Bibliographic record
Abstract
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.”
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".