Mastering the Risky Business of Public-Private Partnerships in Infrastructure
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
Investment in infrastructure can be a driving force of the economic recovery in the aftermath of the COVID-19 pandemic in the context of shrinking fiscal space. Public-private partnerships (PPP) bring a promise of efficiency when carefully designed and managed, to avoid creating unnecessary fiscal risks. But fiscal illusions prevent an understanding the sources of fiscal risks, which arise in all infrastructure projects, and that in PPPs present specific characteristics that need to be addressed. PPP contracts are also affected by implicit fiscal risks when they are poorly designed, particularly when a government signs a PPP contract for a project with no financial sustainability. This paper reviews the advantages and inconveniences of PPPs, discusses the fiscal illusions affecting them, identifies a diversity of fiscal risks, and presents the essentials of PPP fiscal risk management.
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.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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