“Shotitwo First!”: Unraveling Global South Women’s Challenges in Public Transport to Inform Autonomous Vehicle Design
Bibliographic record
Abstract
We call attention to the challenges associated with Global South women’s safety in public transportation and investigate the potential of autonomous vehicles (AVs) in providing them with greater mobility and broader opportunities. In a mixed-methods study with Bangladeshi women (n=23), we explored their safety issues, including sexual harassment and assault, to inform AV design, especially for shared rides. Our focus group findings revealed women’s distressing experiences of abuse and undertaken safety measures in public transport of Global South. We conducted co-design sessions utilizing virtual reality (VR) scenarios and investigated participants’ perceptions of potential AV designs addressing unique safety concerns and transportation challenges. Participants suggested prioritizing their own safety, achieved through design justice of equitable AV, over the current, often ineffective, retributive justice. Our work contributes to AV design, ICTD, and feminist HCI by suggesting implications for designing community-based and culturally contextual transportation infrastructure for Bangladeshi women and similar other communities.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".