Familial and Educational Attitudes towards Children with Special Needs in China and Thailand
Bibliographic record
Abstract
Attitudes towards children with special needs vary around the world and may vary in different parts of the same country. For most Buddhist Thais, the birth of such a child indicates sins committed in the past and karmic consequences. For those of Sino-Thai lineage, such a child may indicate good fortune to come. Meanwhile, in China, many parents will refuse to accept a clinical diagnosis and will return to consult doctors numerous times in the hope of obtaining a second opinion. They may refuse to acknowledge the situation until the child is seven years old and able, therefore, to be admitted to a school specializing in treating children with special needs. Across Thailand, teachers have comparatively high social status and a greater proportion of the national budget is spent on education than in China (although there remain significant problems in the Thai education system). Spending on education for children with special needs is also lower in China and the Chinese system requires teachers to advance through knowledge acquisition, which means few teachers are able or willing to teach children with special needs. By contrast, the Thai system attempts to imbue teachers with an awareness of ethics and encourages a loving relationship between teachers and children and inculcate cooperation among students. This paper is based on qualitative research in both countries concerning the treatment of children with special needs and the production of teachers to help teach them. Insights are drawn and some initial policy recommendations made.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".