Users’ safety perceptions from crime in relation to park type and user gender in Mexico.
Bibliographic record
Abstract
While parks hold potential as inclusive spaces for promoting physical activity, perceptions of safety from crime may affect their use, especially in low-to middle-income countries. Safety perceptions may be shaped by gender and park type; however, these relationships have not been explored in Mexico. The aim of this study was to explore associations between safety perceptions and park type by gender. This was a cross-sectional and descriptive study. We assessed perceptions of safety from crime in Mexican adult park users in Jalisco state. Six parks were classified into three categories: 1) Metropolitan parks with controlled gate access (gated), 2) Metropolitan parks without controlled gate access (open), and 3) Linear parks (linear). We ran binary logistic regression models to investigate the association between safety perception and park type, and safety perception and gender. We found that men were more likely to feel safe than women, regardless of park type, and users of linear parks were more likely to feel safe than users of gated parks, regardless of gender. Safety perception is related to park type and park user gender. Future studies should explore which specific park attributes are influencing park user safety perception and how to address gender disparities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".