“I Bet You Don’t Get What We Get”: An Intersectional Analysis of Technology-Facilitated Violence Experienced by Racialized Women Anti- Violence Online Activists in Canada
Why this work is in the frame
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Bibliographic record
Abstract
Despite growing attention to violence that women face in online settings, a relatively small proportion of academic work centres on the experiences and perspectives of racialized women in Canada. Informed by an intersectional framework, I draw on semi-structured interviews with nine women across Canada, all of whom are involved in anti-violence online activism, about their experiences of technology-facilitated violence (TFV). Their experiences revealed less prominent narratives, including instances of TFV beyond instances of intimate partner violence (IPV) and beyond sources of anonymous trolling by supposed white men, such as violence perpetrated by peers, white women, and racialized men. In this article, I also include reflections by the interviewees on violence they unexpectedly perpetrated through their online content. These perspectives demonstrate how varied and complex experiences of TFV are beyond instances of IPV and sexual violence. I conclude that when we leave out intersectionality as an approach that centres marginalized groups and broadens our understanding of violence, we are missing out on these more complex experiences of TFV that women face. Thus, I suggest that, to best tackle TFV, policy recommendations and legal remedies need to consider TFV through an intersectional lens.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it