Social Movement and Mental Health of South Korean Women Sexual Violence Survivors, 2012–2019
Bibliographic record
Abstract
Objectives. To examine whether the #MeToo movement influenced depressive symptoms among women in South Korea with a history of experiencing sexual violence. Methods. We used data from a nationally representative sample (n = 4429) of women 19 to 50 years of age who participated in the Korean Longitudinal Survey of Women and Families between 2012 and 2019. A difference-in-differences model was used to estimate within-person changes in depressive symptoms attributable to the #MeToo movement across women with and without a history of experiencing sexual violence. Depressive symptoms were measured with the Center for Epidemiologic Studies Depression Scale (CESD). Results. After adjustment for potential confounders, the #MeToo movement led to a 1.64 decrease in CESD scores among women with a history of experiencing sexual violence relative to women without such a history. Conclusions. Our findings suggest that the #MeToo movement in Korea led to reduced depressive symptoms among women with a history of experiencing sexual violence. Public Health Implications. Despite the progress of the #MeToo movement, there are still judicial and institutional problems that can revictimize sexual violence survivors. Further policy changes will likely improve the mental health of survivors. (Am J Public Health. 2022;112(9):1337–1345. https://doi.org/10.2105/AJPH.2022.306945 )
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".