Beyond ‘one size fits all’: how local conditions shape PPP-enabling field development
Bibliographic record
Abstract
The use of public–private partnerships (PPPs) for infrastructure development has received significant scholarly attention of late, but there remains a need for more work at the programme level. Specifically, there is a need for work that recognizes the way that PPP programmes are implemented differently in different regions, thereby progressing beyond an effectively ‘one size fits all’ view of PPP programmes. In response, this paper offers a comparative analysis of the historical development trajectories of three contemporary PPP programmes: in British Columbia (BC) (Canada), Victoria (Australia) and South Africa. We begin by recognizing the role played by the UK's private finance initiative as a programme model, and then show how this model was adapted and modified in each of our cases, leading to very different field structures. The study uses a grounded theory building approach and draws heavily on theories of institutional change and structuration. There are two main contributions from this study: (1)...
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".