A review of the impact of Canadian law, policy and P3 practice on the case for procuring capital-intensive infrastructure services via P3s
Bibliographic record
Abstract
This dissertation investigates the advantages of procuring capital-intensive infrastructure services via Public-Private Partnerships (P3s or PPPs) – cost and time savings and; innovation and high levels of efficiency – accounting for these advantages by reference to the underlying legal provisions and principles that facilitate them; and in this process highlights two significant directions in which Canadian P3 law, policy and practice has evolved – the enactment of P3 legislation and/or the formulation of non-statutory P3-related policy; as well as the establishment of legal institutions that promote and/or facilitate P3 procurements. The dissertation also addresses key arguments raised against P3s, by reference to aspects of Canadian law, policy and P3 practice. The research methodology comprises a detailed review of legal and non-legal sources. The implication of the research findings is that, given the foregoing developments in Canadian P3 law, policy and practice, the key arguments canvassed against P3s are overstated and lacking in merit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.031 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".