Hostile Masculinity and Emotional Negativity as Pathways to Hostility Toward Women
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
Hostility toward women is frequently examined as a risk factor for sexual or physical aggression against women, but it is also associated with other violent offenses. However, despite its relevance, research on the etiology of this misogynistic attitude is lacking. Thus, the aim of our study is to explore the effect of developmental and psychological factors on hostility toward women and cognitive distortions associated with it. Partially inspired by Malamuth’s (1996) confluence model of sexual aggression, we will investigate the mediating role of “hostile masculinity” (i.e., personality characteristics associated with callousness and antisociality) and “emotional negativity” (i.e., depressive and anxious emotional experiences) in a multifactorial model of hostility toward women. We tested our etiological model on a Canadian sample of sexual aggressors of women (n=200), using structural equation modeling (SEM). Results indicated the presence of several pathways from childhood victimization leading to hostility toward women through hostile masculinity and emotional negativity. Findings will be discussed along with their theoretical implications.
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 | 0.001 |
| 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) | 0.001 | 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