Refugee Children’s Resilience: A Qualitative Social Ecological Study of Life in a Camp
Bibliographic record
Abstract
Abstract A social ecological theory of resilience shows that the process of resilience not only depends on an individual child’s personal traits but also on the capacity of the child’s environment to provide the resources required for the child to use these traits to achieve psychological and physical wellbeing in contexts of adversity. The aim of this study is to investigate how refugee mothers influence their children’s developmental outcomes despite exposure to the large number of risk factors they experience living in a refugee camp. Ten Syrian mothers of children aged 5–7-years-old participated in both semi-structured interviews and focus groups conducted while they were living in a refugee camp in Turkey. Using an inductive thematic analysis, findings show that participants found unconventional ways to build their children’s social capital, provide an education and maintain culturally grounded values and beliefs when facing with multiple distal and proximal challenges. These findings highlight the importance of understanding resilience as a psychosocial and interactive process occurring at multiple systemic levels (in this case, child, mother, and camp). Improving the functioning of larger systems may be an efficacious way of creating stable and nurturing environments for children to experience greater resilience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.011 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".