China's Economic Stability Through Management of Rural Education Development: Condition and Possibilities
Bibliographic record
Abstract
As the largest developing country, China has made significant achievements in the battle against poverty in a short period.The key point lies in the targeted rural poverty alleviation policies with Chinese characteristics, for which educational poverty alleviation is the fundamental guarantee.Educational poverty alleviation in rural povertystricken areas is mainly to improve the total amount and quality of rural human resources with the adoption of various education-based human resource development models.The development of rural human resources is conducive to increase the income of rural poverty families and then achieve sustained poverty elimination.In this study, we argue that preschool education could promote economic growth in rural poverty-stricken areas through internal and spillover effects based on human resource development.Internal effect is mainly manifested in its direct effect on improving the quality of human resources, for example, to block the inter-generational transmission of poverty by cultivating high-quality laborers in the future.While, the spillover effect is mainly reflected in the increase in the total amount of human resources, such as transforming the original child caregivers (female and elderly) into productive laborers.Additionally, the teacher training model for preschool education in rural areas could also promote rural human resources development by enabling plenty of surplus laborers to participate in preschool education.To the best of our knowledge, this study is the first to analyze the effects of preschool education on achieving sustained poverty elimination in the post-poverty era from a new perspective of human resources development with the combination of the seventh population census bulletin and the three-child policy recently released in China.Our findings could provide references for other developing countries that are committed to poverty alleviation, and also are conducive to accelerate the process of establishing inclusive preschool childcare and education service system in China to achieve sustainable rural development.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".