Gender Stereotypes & Rape Myths: Investigating the Impact of Psychological Androgyny
Bibliographic record
Abstract
Previous research has found evidence that psychological androgyny—possessing high levels of both masculine and feminine characteristics—is related to fewer sexist beliefs in children (Pauletti et al., 2017). However, this is yet to be examined in an older cohort. Given that sexist beliefs are related to higher endorsement of rape myths (Johnson & Johnson, 2021), the purpose of the current study is to examine whether psychological androgyny is related to lower endorsement of rape myths in a sample of emerging adults. The sample included 83 undergraduate students (ages ranged from 18 to 37) recruited from Huron University College in London, Ontario. Participants completed an online survey in which measures for gender role category, rape myth acceptance, self-esteem, peer conformity, and peer pressure were administered. An analysis of covariance revealed that rape myth acceptance differed significantly by gender role category when controlling for self-esteem, peer conformity, and peer pressure. Further comparisons indicated that the androgynous and undifferentiated groups displayed significantly lower scores than the masculine-typed group. Implications and directions for future research are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".