Selection of PPP Projects in China Based on Government Guarantees and Fiscal Risk Control
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Public-Private Partnership (PPP) is an effective investment channel for government to provide public services. PPPs have the advantage of transferring some project risk to the private sector. They also imply that the public sector should establish appropriate laws and regulations to enable government departments to effectively avoid the emergence of new fiscal risks, which may affect the sustainability of fiscal budgets. This paper expounds the fiscal risks implied by PPP projects in China and the status of government guarantees in various forms of PPP projects; chance-constrained goal-programming (CCGP) is used to simulate government project selection under budget and risk control constraints. The analysis takes fiscal space, the expected costs and benefits of government guarantees, and the possibility of excess government subsidies into consideration. Constrained by fiscal risk minimization and budget limitations, PPP projects with government guarantees can maximize social-economic net present value and simultaneously optimize welfare. The paper also puts forward corresponding policy recommendations based on the research findings.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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