The Development of Preschool Education Achievements, Problems and Policy Recommendations of Tibet
Bibliographic record
Abstract
This paper shows the development of preschool education in Tibet through analyzing the statistical data from Statistical Yearbook of National Education, Statistical Yearbook of National Education Funding and Statistical Yearbook of Tibet and field investigations. It is found that the preschool education in Tibet has developed rapidly for the support of government, and achieved the following development effectiveness: education resources have increased; preschool education funding increased rapidly; the development tends to be balanced between urban and rural areas; bilingual education developed rapidly, and more attention is paid to education equality. However, there are still many problems to be solved in the future. The study has indicated that the quality of preschool education in ethnic areas is low, the local government does not play an active role in developing preschool education and the preschool education is unsuitable for local features. Therefore, more attention should be paid to the preschool education in ethnic areas as well as to the quality of the quantity and the theory researches. The government should also develop the bilingual education in Tibetan scientifically.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".