Tripartite Risk Game Analysis on Public Private Partnership Projects of High-Speed Rail from the Perspective of Bank
Bibliographic record
Abstract
The bank is a leading funder and a primary risk bearer in public private partnership (PPP) projects of high-speed rail (HSR). This paper explores the risk sharing of HSR PPP projects among three parties: the public sector, the private sector, and the bank. From the perspective of the bank, a comprehensive risk evaluation index system (EIS) was established, involving 37 risk factors in 4 stages. Meanwhile, the fuzzy evaluation method was used to calculate the center of gravity (COG) values. On this basis, a tripartite static game model was established based on risk preference. Then, the equilibrium point set of risk sharing was summarized by analyzing the payment matrix of the game. The results show that the bank-oriented comprehensive EIS for the risks in HSR PPP projects can effectively reduce the bank’s capital risk, and the reasonable risk sharing among the three parties is greatly affected by the game mechanism based on risk preference and deterrent effect.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".