Work-related injuries among Syrian refugee child workers in the Bekaa Valley of Lebanon: A gender-sensitive analysis
Bibliographic record
Abstract
BACKGROUND: Syrian refugees in Lebanon have endured increasing hardships since the onset of the Syrian war in 2011, with many resorting to child labor. Working refugee children endure socioeconomic deprivation and harsh working conditions. This study explores the relationship between working conditions and the reporting of injuries among male and female Syrian refugee children in Lebanon and the related gender differences. METHODS AND FINDINGS: A cross-sectional survey of Syrian refugee children working in the Bekaa Valley of Lebanon was conducted in 2017. Face-to-face interviews with children (8 to 18 years) collected sociodemographic information and testimonies of their work experiences. Logistic regression tested the association between reporting of injuries and risk factors including school enrolment, field of work, means of transportation to work, age started working, number of working hours, multiple jobs, work pressure and hazards, and abuse. Analyses were stratified by gender. Of the 4090 surveyed working children, the majority reported working in agriculture (75.8%). Around a third (31.4%) reported being injured at work with a higher proportion in males. The most common reported injuries were cuts and wounds (44.9%), with males showing a higher proportion for all types of injuries compared to females. Nearly one fifth of reported injuries (19.8%) required medical attention in a hospital, with males reporting higher proportions than females for most types of injuries. The study findings revealed the association of multiple risk factors with an increased odds of reporting an injury, which included working in more than one job (AOR, 1.71; CI, 1.20-2.43; p = 0.003), working under pressure (AOR, 1.64; CI, 1.36-1.97; p<0.001), the use of sharp or heavy objects (AOR, 1.88; CI, 1.58-2.24; p<0.001), and experiencing physical abuse at work (AOR, 2.46; CI, 1.97-3.08; p<0.001). The odds of reporting an injury increased with every additional hour of work per day (AOR 1.08; CI, 1.02-1.14; p = 0.006). Most of these findings persisted in the male and female stratified models, with few exceptions. Males who went to work in a pickup truck had significantly lower odds of being injured than those who walked (AOR, 0.65; CI, 0.51-0.83; p = 0.001); this finding did not reach significance for females. Having longer work hours per day was significantly linked to higher odds of injury for females (AOR, 1.07; CI, 1.02-1.12; p = 0.008); but not for males. The main limitations of this study were its cross-sectional design and the use of self-reported variables. CONCLUSIONS: This study is the first to obtain direct testimony on work-related injuries and working conditions, exploring gender differences, among Syrian refugee children in Lebanon. Results demonstrated the association between the occurrence of injury and multiple risk factors highlighting their strenuous working conditions, with some differences detected between males and females. Many injuries can be prevented through direct safety interventions and proper implementation of child labor policies. Multidimensional interventions are essential to address the complex evolving challenges facing refugees.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".