Bibliographic record
Abstract
Abstract Crime and gentrification represent hot button issues in racially diverse neighborhoods. Drawing on three and a half years of ethnographic fieldwork, this book provides a detailed analysis of community conflict in Rogers Park and Uptown, two Chicago neighborhoods. The book shows how competing views about neighborhood change divided residents into two political camps, which prioritized either the fight against crime or the fight against gentrification. This division frequently materialized as a type of racial conflict, because antigentrification activists and their allies charged that grassroots anticrime initiatives were, in truth, barely covert racist practices that were meant to foster racial displacement and marginalization. Chapter by chapter, the book traces these conflicts in different areas of community life. It examines the strategies of public safety work that residents used to fight crime and how their efforts contributed to gentrification; how antigentrification activists resisted criminalization and gentrification; how politicians sought to actively use or downplay community divisions in their electoral campaigns; and how residents of different racial and ethnic backgrounds positioned themselves in these battles.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.119 | 0.030 |
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".