Growing healthy children and communities: Children’s insights in Lao People’s Democratic Republic
Bibliographic record
Abstract
A diverse group of 103 children aged 7-11 years old living in family and residential care in rural and urban settings in two northern provinces in Lao People's Democratic Republic participated in group discussions using images and community mapping. Children's identified sources of risk and protection illustrate primary public health and protection concerns and resources. Young children worried about lack of hygiene, unintentional injuries, corporal punishment, and domestic violence. They also expressed concern about gambling and children sleeping in the streets, even if they had never seen any of the latter in their communities. In contrast, food and shelter; artistic, religious, and cultural practices; supportive interpersonal relationships; and schooling largely evoked feelings of safety and belonging. Images that prompted conflicting interpretations surfaced individual and contextual considerations that nuanced analysis. Researchers and decision-makers will benefit from using this developmentally appropriate, context-sensitive child-centred visual method to elicit young children's views of risk and protection. It may also serve as a tool for public health education. Involving young children in the initial selection of images would further enhance the efficiency of the method.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 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".