‘Stepping back’ as researchers: How are we addressing ethics in arts-based approaches to working with war-affected children in school and community settings.
Bibliographic record
Abstract
There is a need for an ethically responsible means of conducting arts-based research with children affected by global adversity, including children affected by war.The multiple effects of war on children remains a global issue.While there are many approaches to working with waraffected children, participatory arts-based methods such as photovoice, drama, and drawing are being increasingly relied upon.However, what are the ethical issues and how are researchers and practitioners taking up these issues in school, community, and "on the street" settings?By reviewing the literature on ethical issues that may arise when working with children through arts-based methods, this article identifies four critical ethical issues that represent specific challenges in relation to children affected by war: (1) informed consent; (2) truth, interpretation, and representation; (3) dangerous emotional terrain; and (4) aesthetics.The article highlights current gaps in the research and poses several unanswered questions in arts-based research with war-affected children.
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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 | 0.360 | 0.373 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.044 | 0.200 |
| Scholarly communication | 0.067 | 0.078 |
| Open science | 0.010 | 0.049 |
| Research integrity | 0.031 | 0.044 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".