Breaking the silence: exploring women’s experiences of participating in the #MeToo movement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
#MeToo is a digital social movement that has garnered significant attention from feminist scholars since the hashtag obtained viral fame in 2017. Nonetheless, how survivors of sexual violence experience participating in #MeToo remains an understudied question. In this paper we analyze vlogs posted on YouTube under the hashtag to understand how women represent the affordances and drawbacks of participating in the movement, and how they imagine their experiential narratives may affect other survivors. We argue that vloggers represent #MeToo as a forum for breaking the culture of silence that structures sexual violence. As they narrate their experiences, vloggers challenge silencing mechanisms by cultivating voice, resistance strategies, and survivor solidarity, while encouraging viewers to similarly examine their own experiences. Vloggers also identify the emotional burdens associated with disclosure and the damages incurred by confronting rape myths and the entrenched denial of perpetrator guilt as drawbacks of participation.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it