Public‐Private Partnerships: The Way They Were and What They Can Become
Bibliographic record
Abstract
Abstract Infrastructure PPPs are now main‐stream. Both partnership language and its contractual forms have evolved over the past few decades, though. Compared to early optimistic promises, we now have a more nuanced and balanced view of what PPPs are and what they can achieve. Indeed, modern PPPs are tied more to seeking economic growth and political success rather than demonstrating ‘one‐best‐way’ to deliver efficient infrastructure. This article traces where the infrastructure PPP idea has come from and what it is now becoming. It takes a global perspective and places Australian and international experience in this context, particularly through the global financial crisis. It concludes that PPP can become an integrated part of infrastructure development around the world, assuming learning occurs from past experience. It presents several lessons on deepening partnerships; on the multiplicity of the PPP ‘model’ and its ingredients; on policy learning and on governing infrastructure in the medium term. And it also concludes that not only does the PPP brand today still offer manifold possibilities, even more public policy experimentation is currently warranted.
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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 | 0.027 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.034 | 0.043 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".