Transformative Change and Measuring Success: Public-Private Partnerships in British Columbia, 2001-2005
Bibliographic record
Abstract
Public-private partnerships can be understood to be instruments for meeting the obligations of the state (things that there has been a strong social consensus that the state ought to do) that are transformed so as to involve private property ownership as a key element in the operation of the instrument. The word partnership is important and not just a euphemism for hiding a privatization (at least it ought not to be). Partnership means a relationship based on common goals where both entities share benefits and contribute resources over the long-term for mutual advantage and out of a sense of commitment. In a design-build-finance-operate (DBFO) public-private partnership, the state agency sponsoring the development hires either a single company (or consortium of companies) to, as the term suggests, meet the full extent of its public obligation by determining how best to meet the obligation, designing and building the necessary infrastructure and then operating it. This paper looks at the development of three DBFO public-private partnerships in and around Vancouver, British Columbia, asking what the likelihood is that the public will benefit from decisions to employ this procurement model. When using a definition of benefit that is broader than simply saving money, it is possible that these projects can provide greater benefits than a traditional public procurement, although the managers of two of the projects will likely face greater difficulties in doing so than the managers of the third one.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".