Towards a richer understanding of school-age children’s experiences of domestic violence: The voices of children and their mothers
Bibliographic record
Abstract
Millions of children are exposed to domestic violence. How children negotiate and make sense of living with domestic violence is still under-researched. This study sought to capture the dual-perspectives of school-aged children and their mothers, to develop a richer understanding of children's experiences of domestic violence, using a community-based sample. A qualitative research design was employed, with interpretative phenomenological analysis used to interpret the data. Five school-aged children and three of their mothers participated in the study. Two master themes are discussed from the analysis of the children's perspective: domestic violence through the eyes of children; and learning from children's experiences. Two master themes are discussed from the analysis of the mothers' perspective: reflecting on the child in the context of domestic violence; and learning from mothers: insights, support and services. The crucial importance of the mother-child relationship in shaping children's experience of domestic violence was illustrated in both the perspectives; a finding which may have important implications for the development of interventions. It was also evident that children as young as eight were able to powerfully articulate their experiences of domestic violence.
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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 | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".