“Fox-like. One eye open, one eye closed”: child supervision among Syrian refugee mothers in Canada
Bibliographic record
Abstract
When children live through violent conflict and forced displacement, the associated disruptions in their environment can profoundly affect their wellbeing and development, undermining stability and family cohesion essential for healthy growth. Adequate child supervision is an important component of supportive parenting but is understudied in the refugee migration context. Guided by the United Nations Convention on the Rights of the Child (CRC) (1989), which emphasizes the protection, provision, and participation of children as rights-holders, this study explored how Syrian refugee mothers resettled in Canada between late 2015 and 2017 perceived and practiced child supervision. Using a cross-sectional, qualitative design, we conducted semi-structured interviews with 20 mothers (half government-assisted refugees and half privately sponsored refugees) to examine their parenting across four migration stages: pre-conflict Syria, pre-flight conflict Syria, transit in various countries, and resettlement in Canada. Participants came from diverse religious and cultural backgrounds and spent varying times in transit (between 2 months to 5 years). Mothers' narratives revealed how their approaches to children's provision, protection, and participation evolved, shaped by material resources, social networks, and risks at each stage. Grounded in a critical children's rights framework, the analysis of mothers' daily negotiations highlights the dynamic and context-dependent nature of children's rights, and the interconnections and tensions between provision, protection, and participation in child supervision. This study contributes to a deeper understanding of how refugee mothers navigate and uphold children's rights throughout migration trajectories, advocating for policies and interventions that recognize these dynamic processes and the critical role of caregivers in ensuring children's dignity and wellbeing.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".