‘Difficulties come to humans and not trees and they need to be faced’: A study on resilience among Indian women experiencing intimate partner violence
Bibliographic record
Abstract
BACKGROUND: Not much is known about factors that contribute to resilience among women facing intimate partner violence (IPV), particularly from countries where patriarchy predominates. This qualitative study aimed to gather the perspectives of Indian women self-identified as resilient in the face of IPV and tried to understand the strategies and resources that helped them to maintain or regain resilience. MATERIALS: Data were collected from 16 consenting women who reported IPV and whose husbands were being treated for alcohol problems at a psychiatric centre in Bangalore, India. A semi-structured guided interview format that aimed at understanding factors that enabled them to feel resilient despite IPV in their challenging circumstances was used to gather narratives from the participants. DISCUSSION: Six themes were identified using QSR NVivo software. They were as follows: the support of women, men and family; personal attributes; dignity and work; being strong for the children; and faith in God. Among these women, supportive social networks, personal attributes and aspirations were major clusters contributing to resilience. CONCLUSION: Attention to these factors may provide an important, strengths-based perspective for interventions to enhance women's resilience when facing IPV.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".