Exploring the Success of Social Infrastructure Public Private Partnerships: The Complex Case of Bridgepoint Active Healthcare in Ontario, Canada
Bibliographic record
Abstract
Notwithstanding the deployment of tools to standardize delivery processes, public–private partnerships (PPPs) have encountered significantly different experiences across a broad spectrum of applications during their long-term contractual phase—including those in Ontario Canada, one of the world’s most active PPP markets. This article conducts an in-depth case study of the PPP for the new Bridgepoint Active Health care Hospital, an award-winning 464-bed hospital and administration facility delivered using a design–build–finance–maintenance PPP. This article reveals the role of personalities, relationships, and strong leadership in bringing a successful project to fruition in the face of complex, intersecting challenges. In this context, the PPP is only one variable in explaining the overall success of this complex and highly visible social infrastructure project.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.041 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".