Calculation and Driving Mechanism of Spatio – Temporal Evolution of Rural Occupational and Residential Functional Efficiency in Jilin Province Based on Geographic Detection Modeling
Why this work is in the frame
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Bibliographic record
Abstract
Rural population loss is a common phenomenon in northeast China, even in the whole country and all over the world, has signi icantly hindered economic and social development in rural areas, leading to a weakening of growth momentum and even stagnation.In view of this, this paper focuses on Jilin Province, a typical region, and uses key data such as rural resident population, rural employed population, and job supply in the region from 2008 to 2021.Through the comprehensive application of spatial autocorrelation analysis methods and the geographical detector model, it deeply analyzes the spatio-temporal evolution patterns of the rural occupational and residential function-ef iciency at the county scale in Jilin Province, the trade-off and synergy relationships, and the driving mechanisms behind them.The results show that: the synergy level of the rural occupational and residential function-ef iciency index in Jilin Province has gradually increased over time; the index shows a steady upward trend and spatial clustering characteristics; the index is in luenced by a variety of driving factors, and the mechanisms of these factors vary.These indings will help the government formulate sustainable rural development policies and provide a useful reference for promoting comprehensive rural revitalization and development.
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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 | 0.002 | 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 it