A Thousand Catcalls: Survivors’ Experiences of Sexual Violence in Online Dating
Bibliographic record
Abstract
There is growing academic interest in the leisure spaces of online dating as a specific avenue of technology-facilitated sexual violence (TFSV). Yet, limited attention is paid to survivors’ experiences and understandings of sexual violence intermediated by dating apps. Using feminist standpoint theory and an intersectional lens, in-depth interviews were conducted with 15 current and former dating app (e.g. Tinder, Grindr) users of diverse identities and backgrounds who previously experienced sexual violence. Sexual violence was found to take a multiplicity of forms spanning the “online-offline” continuum that often co-occur and mutually reinforce their effects, including sexual assault threats, image-based harassment, gender/sexuality-based hate speech, and in-person sexual coercion and/or aggression. Depending on the experience frequency and severity, psycho-social outcomes range from indifference/mild annoyance to emotional trauma and social withdrawal. Findings underscore the profound personal and collective impacts of TFSV and the urgent need for coordinated, multisectoral responses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".