Analysis of the Synergistic Effect of Rural Sustainable Development and Rural Revitalization Policy in Guangdong Province
Bibliographic record
Abstract
Guangdong province, as the center of China's economy and culture, has always had a unique position in the rural development. In recent years, with the proposal of the rural revitalization strategy, how to implement this policy in Guangdong and ensure that it is combined with sustainable development has become the focus of the academic and practical circles. This study aims to deeply explore the current situation of sustainable development in rural areas in Guangdong Province and the practice and synergies of rural revitalization policies. Through a literature review and empirical analysis, we systematically reviewed the historical evolution, current situation and challenges and problems encountered in Guangdong in practice. It is found that in the process of promoting rural revitalization and sustainable development, Guangdong province has successfully combined the two, and achieved significant economic, social and cultural benefits. But at the same time, it also faces some challenges, such as ecological and environmental protection and farmers' income gap. The conclusion points out that Guangdong's exploration provides valuable experience for other regions, but also emphasizes important issues to be addressed in future research and policy making. The innovation of this study lies in the first in-depth discussion of the synergistic effect of rural revitalization and sustainable development in Guangdong, which provides a new perspective and thinking for the research in related fields.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".