Application of GIS in Land Policy and Planning Strategies in Rural Revitalization
Bibliographic record
Abstract
In recent years, there has been a growing emphasis on reviving rural areas in China, which has become a crucial strategic direction for the nation's economic and social development. Currently, rural revitalization is a major endeavor in China, and the successful implementation of land policy and planning strategies is crucial to its achievement. This study seeks to examine the use of Geographic Information System (GIS) in crafting land policy and planning strategies for rural rejuvenation. By harnessing GIS technology, a thorough evaluation and analysis of rural land resources can be undertaken, furnishing a scientific basis for formulating land policy. Furthermore, Geographical Information Systems (GIS) provide opportunities for spatial analysis, simulation, and decision support capabilities to implement rural land policy and planning strategies. Nevertheless, the use of GIS technology presents challenges and limitations in terms of data acquisition and technological implementation. To promote the sustainable development of the rural economy, future research efforts should concentrate on further enhancing the utilization of GIS technology in rural revitalization.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".