Personality Traits and Severity of Wife Abuse among Iranian Women
Bibliographic record
Abstract
The main purpose of this study was to determine the relationships between personality traits and severity of wife abuse among Iranian women in Tehran city in Iran. The study involved 398 women who sought treatment at 4 selected hospitals by using multistage stratified sampling technique. Conflict Tactic Scale (CTS2) and Five-Factor Personality Inventory (NEO-FFI) were used to measure severity of wife abuse and personality traits respectively.Findings showed that out of 398 women studied, 42.5% received minor abuse and 43.5% received severe abuse. Severity of total wife abuse was positively related to neuroticism personality and negatively related to extraversion, agreeableness and conscientiousness. However, no significant relationship was note for total wife abuse and openness personality. The result of multinomial logistic regression indicated that neuroticism personality trait was a significant predictor of minor and severe total abuse. The results of the current study highlighted the importance of personality traits in explaining the severity of wife abuse in Tehran, Iran. Therefore, strategies to prevent and intervene cases of abuse among wives in Tehran, Iran should take into consideration individual’s personality traits.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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 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".