Empirical Studies on the Relationship between Households’ Trust in Government and Agricultural Land Tenancy-Based on the Households Survey in Four Provinces
Bibliographic record
Abstract
In the premise of the separation of ownership and use right of land in China’s rural areas, agricultural land tenancy will be inevitably subject to the influence from the grass-roots government. In order to analyze the role of the trust in government from farmers in land tenancy, we have made a field research on 1305 households in 36 villages randomly selected in Shandong, Hubei, Gansu and Guangxi Provinces and got first-hand data in the year of 2010.In this thesis, we made statistical descriptions of households’ trust in government and agricultural land tenancy in field survey areas firstly, and then found that the formers have significant effect on the latter from the empirical analysis. Furthermore, as with the increase of the degree of farmers’ trust in government, the ratio of the land tenancy net of final use of the land will become less and less, which means a greater possibility of land leasing. In another word, the more the households’ trust in government is, the more inclined the land tenancy will be. In this paper, we have explained the conclusions above and given the relevant policy recommendations from the conclusions.
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 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 | 0.001 | 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".