A narrative inquiry into experiences of Syrian refugee families with children living with disabilities
Bibliographic record
Abstract
Purpose Children who are refugees and who live with disabilities are among the most at-risk groups for marginalization due to compounded disadvantages from the intersection of risk factors such as refugee status and disability status. Despite their high risk, there is no systematic data collected on this group and scant literature on the topic contributing to a feeling of invisibility. The purpose of this study is to better understand the experiences of Syrian refugee families with children living with disabilities. Design/methodology/approach The authors conducted a narrative inquiry into the experiences of two Syrian refugee families with children living with disabilities. Narrative inquiry is a way to understand experience as a storied phenomenon. Findings In attending to the families’ stories of their experiences across time, place and social contexts, two narrative threads resonated across their experiences including waiting and a struggle for agency as well as disruption and continuity. Research limitations/implications Narrative inquiry does not produce generalizable results but, rather, gives insight into the unique experiences of individuals. Originality/value To understand the complexities of the experience of a refugee family with a child living with disabilities, attending to their lived and told stories is essential.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".