Female gender, sexist maltreatment, adverse childhood events, and psychological symptoms: A case of omitted-variable bias.
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to examine the relationship between gender and symptomatology as potentially mediated by exposure to sexism and childhood adversity. METHOD: Using an online sample of 498 women and men, structural equation modeling was employed to test these potential direct and intermediary associations. RESULTS: A direct path from female gender to symptomatology in Model 1 had acceptable fit characteristics. However, this relationship was no longer present once exposure to sexism and adverse childhood experiences (ACEs) were added in Model 2. Instead, female gender was associated with exposure to sexism and childhood adversities, which, in turn, were related to symptomatology. Also significant in Model 2 was a path from male (but not female) gender to symptomatology once sexism and ACEs were taken into account. Follow-up analyses of variance revealed that the change from female to male prediction of symptoms was a function of the intermediary effects of exposure to sexism, but not ACEs. CONCLUSIONS: Women's symptomatology may not be uniquely related to their gender, per se, but is significantly associated with their experiences of sexism and childhood adversity. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".