Backlash against the #MeToo movement: How women’s voice causes men to feel victimized
Bibliographic record
Abstract
Three studies examined whether perceived increase in women’s “voice” (i.e., being heard and taken seriously about sexual assault) contributes to perceptions of bias against men. In Study 1, both men and women who perceived women to have a greater voice related to sexual assault, perceived greater victimization of men. This relationship was stronger for relatively conservative participants. In Study 2, relatively conservative (but not relatively liberal) participants who read about #MeToo perceived greater men’s victimization than those in the control condition. Study 3 examined responses to perceiving that men are victimized by #MeToo. For relatively conservative (but not liberal) men, perceptions of men’s victimhood led to less willingness to work alone with a woman and less willingness to combat sexual assault (relative to a control condition). Thus, while the #MeToo movement brings awareness of issues of sexual assault, it also generates a backlash among the more conservative, and may accentuate gender disparities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.010 | 0.008 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.226 | 0.010 |
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; both teacher heads agree on what is shown here.
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".