The Reasons for the Governmental Failure in the Allocation of Industrial Land in China
Bibliographic record
Abstract
The purpose of the research is to analyze the reason that why industrial land is sold in a relatively cheap price and is allocated inefficiently regarding the governmental failure at different levels.Method used is the game theory to evaluate and test three viewpoints.The results show that with respect to the solution for a more reasonable land price and a better land use efficiency,neither the hypothesis that different municipalities strengthen their monopolized role in the land market and improve their techniques of supplying land,nor the assumption that central government promote a more strict administrative supervision and management was supported by the model analysis.A prominent finding is that the Price Floor Policy successfully helps to maintain a certain level of land price given by local government in the context of current institutions.The paper concludes that several drawbacks of the fundamental institution of the industrial land market are noticed,which cause the abnormally cheap industrial land price and low land use efficiency.A possible solution is that government should gradually leave land market more freedom and autonomy.Based on a market with a variety of land suppliers,the problems discussed in this research can be potentially solved.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".