Reaction to and Coping With Domestic Violence by Iranian Women Victims: A Qualitative Approach
Bibliographic record
Abstract
INTRODUCTION: Domestic violence is a continual stressor that motivates its victim to react. The way a woman deals with her husband's violence determine the consequence of the violent relationship. In the present study, a qualitative approach was employed to investigate women's reactions to and ways of coping with domestic violence. METHOD: Semi-structured interviews were conducted in 2014 with 18 women who experienced domestic violence in an attempt to explain how women deal with domestic violence. After the interviews were transcribed word by word, they were explored in the form of meaningful units and encoded as subcategories and categories through inductive content analysis. The reliability and validity of the interviews were measured by an external supervisor. RESULTS: Two categories of reaction and coping were identified through content analysis: passive and non-normative measures and active measures. Passive and non-normative measures included the subcategories of harmful behaviors, retaliation, tolerance, and silence. Active measures included seeking help and advice, legal measures, leaving the spouse, positive and health promoting measures. CONCLUSION: In the present study, ways of coping with a husband's violence among women experiencing domestic violence were divided into two categories: passive and non-normative measures and active measures. These categories confirmed the models of coping with stress in previous studies. Adopting an appropriate approach to dealing with domestic violence is affected by a woman's capacity and beliefs, the dominant culture, intensity of the violence, available social and legal supports, and effectiveness of evaluation measures. To generalize service provision to victimized women, the type of coping and the reason for adopting the chosen approach need to be taken into account.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".