Victimization and Perpetration of Intimate Partner Violence and Substance Use Disorders in a Nationally Representative Sample
Bibliographic record
Abstract
The aim of this study was to examine the relationship between perpetration and victimization of physical and sexual intimate partner violence (IPV) in the past year and substance use disorders (SUDs) in the past year, including alcohol, sedatives/tranquilizers, cocaine, cannabis, and nicotine stratified according to sex. Data were from the National Epidemiologic Survey on Alcohol and Related Conditions. A series of adjusted logistic regression models were conducted. Among men and women, all types of SUDs were associated with increased odds of IPV perpetration (odds ranging from 1.4 to 8.5 adjusting for sociodemographic variables). IPV victimization increased the odds of having all types of SUDs for male and female victims, with the exception of sedatives/tranquilizer abuse/dependence among women (odds ranging from 1.5 to 6.0 adjusting for sociodemographic variables). Substances that had the most robust relationship with perpetration and victimization of IPV included alcohol and cannabis, after adjusting for sociodemographic variables, mood disorders, anxiety disorders, personality disorders, and mutual violence.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".