How Safe Is the Ride? Evaluation of Design and Policy Responses to Women’s Fear of Victimization and Crime
Bibliographic record
Abstract
Fear and anxiety about personal security are important detractors from using public transit. Empirical research in different cities of the Western world has confirmed that fear about crime affects transit ridership. Surveys of the perceptions of transit passengers have revealed a number of issues related to their anxiety about personal security. For one, fear of transit is more pronounced in certain social groups than others. Gender emerges as the most significant factor related to anxiety and fear about victimization in transit environments. Almost every fear of crime survey reports that women are much more fearful of victimization than men. This fear has some significant consequences for women and leads them to utilize precautionary measures and strategies that affect their travel patterns. These range from the adoption of certain behavioral mechanisms when in public, to choosing specific routes, modal choices, and transit environments over others, to completely avoiding particular transit environments, bus stops and railway platforms, or activities (e.g., walking, bicycling) deemed as unsafe.Women’s fear of crime in public spaces has been adequately documented. Research of transit passengers’ perceptions of transit safety has also intensified in response to the recognition that anxieties about crime are impeding travel choices and affect transit ridership and revenue, and guidelines for safer cities and transit environments have been drafted. Some studies incorporate an analysis of gender differences in perceptions of safety on transit; however, the focus is not specifically on women and safety. In contrast, a small subset of studies has focused on women’s concerns and fears about personal safety in transit environments. Criminologists complain, however, that our increased knowledge about the causes of fear has not necessarily translated into nuanced policy responses tailored to the particularities of different groups and physical settings. Additionally, there remains a general lack of knowledge regarding specific female requirements for urban and transit environments. Researchers have argued that this is partly due to the imperceptibility of women and the assumption that women and men are in the same situation and have the same needs.This study focuses on the safety concerns and needs of women riders. The research tasks undertaken included: 1) A review of the literature on women’s fear in public settings; 2) a compilation of survey findings (mostly from Canada and the United Kingdom) presenting the concerns of women passengers on issues of transit safety; 3) a compilation of an inventory of strategies followed in these countries that target women’s safety; and 4) a web-based survey of U.S. transit operators to document the programs and activities they have implemented to make their systems safer for women riders as well as their assessments of the efficacy of these programs. The survey targeted all 249 transit agencies in the United States that operate at least 50 vehicles in peak period service
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".