The whiteness of gay urban belonging: criminalizing LGBTQ youth of color in queer spaces of care
Bibliographic record
Abstract
Chicago’s gay village of Boystown has long been linked with whiteness, and in the past decade, tensions have flared between neighborhood residents and queer and transgender (trans) youth of color, often homeless, who come to Boystown for the many services provided by its lesbian, gay, bisexual, transgender, and queer (LGBTQ) nonprofit organizations, or queer spaces of care. While scholars have attended to community policing in Boystown through the Take Back Boystown movement, the role of LGBTQ nonprofits has yet to be examined in their role of criminalizing queer and trans youth of color in the neighborhood. Through an autoethnographic approach, this paper explores how several nonprofit organizations in Boystown have adopted policing strategies toward the queer and trans youth of color they serve. I argue that community policing has infiltrated these organizations to further defend and maintain an exclusive gay urban space informed by whiteness, which marks and regulates young, Black masculinities and trans femininities as deviant, untrustworthy, and criminal. Racism diminishes the ability for queer spaces of care to fulfill their mandates of supporting queer and trans youth of color, rendering the neighborhood a space of surveillance and furthering a White gay urban belonging that alienates and criminalizes these youth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".