A qualitative study exploring child marriage practices among Syrian conflict-affected populations in Lebanon
Bibliographic record
Abstract
BACKGROUND: Recent reports have suggested that child marriage among Syrians may be increasing as a result of displacement and conflict. This study sought to gather qualitative data about the factors that promote child marriage practices among Syrian refugees in Al Marj area in the Bekaa valley, Lebanon, where the majority of Syrian refugees have settled in Lebanon. The second aim of this study was to generate recommendations on how to mitigate the drivers and consequences of child marriage practices based on the findings. METHODS: Eight focus group discussions were conducted separately with married and unmarried young women and mothers and fathers of married and unmarried women. Furthermore, researchers conducted 11 key informant interviews with service providers and stakeholders to understand how conflict and displacement influenced marriage practices of Syrian refugees in Al Marj community. RESULTS: Although child marriage was a common practice in pre-conflict Syria, new factors seem to contribute to a higher risk of child marriage among Syrian refugees in Lebanon. Respondents cited conflict- and displacement-related safety issues and feeling of insecurity, the worsening of economic conditions, and disrupted education for adolescent women as driving factors. Service providers, young women, and parents also reported changes in some marriage practices, including a shorter engagement period, lower bride price, change in cousin marriage practices, and a reduced age at marriage. CONCLUSIONS: Recommendations for interventions to mitigate the drivers of child marriage and its negative consequences should be built on a clear understanding of the local refugee context and the drivers of child marriage in refugee settings. Interventions should involve multiple stakeholders, they should be adjusted to target each specific context, age group and marital status. For these interventions to be effective, they should be addressed concurrently, and they should be delivered in a culturally sensitive and practical manner.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".