Examining the law enforcement response to complaints of sexual assault on a public transit system
Bibliographic record
Abstract
Women’s safety on public transit systems is an important issue as women around the world typically make up a majority of a public transit system’s ridership, and women are more likely than men to depend on transit for their mobility. Fear while on public transit affects people from many walks of life, and factors that cause fear for many women on transit are poor lighting conditions, desolate stations, and a lack of presence by transit staff or police. The nature of a crowded transit environment also put women at risk of sexual assault. Such assaults are not always reported to the proper authorities. Some transit authorities have conducted public awareness campaigns about sexual harassment on transit while encouraging reporting. This paper examines the Metro Vancouver Transit Police’s response to reports of sexual assault by reviewing the 411 reported sexual assaults from 2013 through 2017. Key findings were that reported incidents reflected peak rush hour travel times, a suspect or person of interest was identified in over half of reported incidents, which coincided with a high rate of sexual assault reports to Crown Counsel.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".