Public–Private Partnerships and the Design Process: Consequences for Architects and City Building
Bibliographic record
Abstract
Abstract Governments are increasingly using public–private partnerships (PPPs) to deliver public infrastructures and facilities. The prime motivation to embark on these partnerships is often to deliver products and services on time and on budget. It is generally assumed that by transferring project risks and responsibilities to private‐sector actors, governments can achieve better value for money. This article provides a novel perspective on the standards applied in PPP endeavors as it examines the tensions between the public management rationale behind value for money on the one hand, and conceptions of design and city building on the other. We focus on planning practice in the Canadian province of Ontario to show that governments apply different understandings of value in PPPs which, in turn, affect the way the design process is run. Architects, who are used to playing the role of master builder in a traditional public infrastructure project, are shifted into a less influential position and struggle with their new role. Furthermore, a different set of priorities applies in the new procurement process. The increasing use of PPPs can thus have significant consequences for city building.
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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 | 0.031 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.040 |
| Scholarly communication | 0.021 | 0.006 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".