Ride-hailing while female: Negotiating China’s digital public sphere
Bibliographic record
Abstract
This research reveals how social media advances gender responsiveness in the context of China’s digital transformation by exploring ride-hailing services, a fast-growing though often under-regulated sector. Specifically, the rise of ride-hailing has been accompanied by incidents of sexual harassment and gender-based violence, leading to social media outrage. Building on Habermas’s concept of the public sphere, this study – perhaps the first to explore the gender dynamics of ride-hailing policymaking in China – centers on the notion of digital public sphere. This study investigates how citizens, corporations, and government agencies have markedly differed in their discourses on gender and safety. Results exhibit that as corporations and government agencies seek technological and legislative solutions to improve safety, Chinese citizen-based activism efforts have amplified gendered perspectives, addressing gender-responsive policymaking. These actors generate discourses that echo various strands of feminism and further cultivate the policy trajectory, including pressuring government agencies to enforce the social accountability of private corporations. This research addresses a pragmatic perspective to demonstrate how liberal, socialist, and cultural feminisms coexist and negotiate in China’s digital public sphere. It aims to enhance one’s understanding of online civic engagement and resulting policy change in contemporary China, enriching the public sphere theory with emerging technology under a contentious political context.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".