Risk Management of Lead and Arsenic Poisoning in Children through Public Participation in Communities near Abandoned Tin Mine, Southern Thailand
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Tamtalu Subdistrict, Bannangsta District in Yala Province, southern Thailand was the site of an abandoned tin mine, and was contaminated by lead and arsenic from the mine tailings. As children are a high risk group from these highly toxic contaminants, this study aimed to identify approaches to reduce children’s exposure in the area. The study was conducted through participatory action research (PAR) to empower the community strengthen sustainable risk management. The participants were local public health officials, public health volunteers, parents of local children and local community leaders. The participants were engaged in activities relating to risk communication, training on exposure prevention, planning of risk management and implementation of the plan. The children’s risks were communicated to the villagers during community meetings. Trainings on how to prevent As and Pb exposure were provided, and preventive strategies planned and implemented. After a six-month period of the intervention, levels of As and Pb in the hair of local children’s decreased significantly (p< 0.01 and p< 0.05, respectively). The parents’ knowledge of how to prevent children from As and Pb exposure increased significantly (p<0.01). The results indicated that PAR can be used to mitigate problems of chronic environmental exposure and poisoning. In addition, the Ottawa Chatter concept can be applied for long-term management. Economic status and effective risk reduction programmes are key determinants for successful implementation of local community-based risk management plans.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it