Lost in translation: a quantitative and qualitative comparison of rape myth acceptance
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
Rape myths (RMs) are a complex set of cultural beliefs and attitudes that support and condone sexual violence, mainly by shifting blame from the perpetrator to the victim. Much empirical attention has been paid to how RMs perpetuate cultural norms that justify sexually assaultive behaviours, with research demonstrating that individuals who have higher rape myth acceptance (RMA) are less likely to believe victims of sexual assault, report their own assault if victimized, and are themselves at an increased risk for sexual violence perpetration. Though several methods exist for assessing RMA, shifting cultural norms make it increasingly difficult to accurately assess RMA using traditional quantitative methods; existing research shows discrepancies in response patterns between qualitative and quantitative examinations of RMAs. In a mock-jury paradigm, university (n = 86) and community-based participants (n = 82) responded to a fictitious police report of sexual coercion between two romantic partners. Results indicated that although respondents endorsed low levels of RMA on a self-report measure (updated IRMA), their qualitative responses endorsed four distinct RMs, such as “she asked for it,” which attributes responsibility for the assault to the victim. Implications and future directions for research will be discussed.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 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 it