‘Broken windows’ and ‘eyes on the street’: how crime affects park and trail use in Chicago’s low-income communities of color
Bibliographic record
Abstract
This study examined how perceptions of crime affected the use of parks and trails for recreation among Latinx residents of two communities in Chicago, IL. Using the ‘broken windows’ and ‘eyes on the street’ frameworks, we examined differences between Little Village, an area experiencing disinvestment, and neighbourhoods around the Bloomingdale Trail, which are gentrifying. We collected data in two phases, including focus groups and interviews with Latinx residents and stakeholders in Little Village (2007), and interviews with Latinx residents of communities surrounding the Bloomingdale Trail (2020). We found that the opportunities for outdoor recreation in these two communities differed. Residents of Little Village showed concerns about the use of parks for recreation, whereas residents near the Bloomingdale Trail seemed to feel safer when visiting the trail. The differences can be attributed to crime and gang activity, upkeep and maintenance of parks and trails, policing and design of natural environments, and neighbourhoods’ socioeconomic status.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".