Continuum of sexual and gender-based violence risks among Syrian refugee women and girls in Lebanon
Bibliographic record
Abstract
BACKGROUND: A myriad of factors including socio-economic hardships impact refugees, with females being additionally exposed to various forms of sexual and gender-based violence (SGBV). The aim of this qualitative analysis was to understand and to provide new insight into the experiences of SGBV among Syrian refugee women and girls in Lebanon. METHODS: The data are gained from a larger mixed-methods study, investigating the experiences of Syrian refugee girls in Lebanon, using an iPad and the data collection tool, SenseMaker®. The SenseMaker survey intentionally did not ask direct questions about experiences of SGBV but instead enabled stories about SGBV to become apparent from a wide range of experiences in the daily lives of Syrian girls. For this analysis, all first-person stories by female respondents about experiences of SGBV were included in a thematic analysis as well as a random selection of male respondents who provided stories about the experiences of Syrian girls in Lebanon. RESULTS: In total, 70 of the 327 first person stories from female respondents and 42 of the 159 stories shared by male respondents included dialogue on SGBV. While experiences of sexual harassment were mainly reported by women and girls, male respondents were much more likely to talk explicitly about sexual exploitation. Due to different forms of SGBV risks in public, unmarried girls were at high risk of child marriage, whereas married girls more often experienced some form of IPV and/or DV. In abusive relationships, some girls and women continued to face violence as they sought divorces and attempted to flee unhealthy situations. CONCLUSIONS: This study contributes to existing literature by examining SGBV risks and experiences for refugees integrated into their host community, and also by incorporating the perceptions of men. Our findings shed light on the importance of recognizing the impact of SGBV on the family as a whole, in addition to each of the individual members and supports considering the cycle of SGBV not only across the woman's lifespan but also across generations. Gendered differences in how SGBV was discussed may have implications for the design of future research focused on SGBV.
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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 | 0.000 | 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) | 0.000 | 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".