EXPLORING OPTIONS TO STRENGTHEN CANADA'S CAPACITY FOR PUBLIC-PRIVATE PARTNERSHIPS
Bibliographic record
Abstract
Canada’s public infrastructure is ageing and the cost of replacing this infrastructure run in the order of hundreds of billions of dollars. Public-private partnerships (P3s) are long-term partnering arrangements between the public and private sector for infrastructure delivery and provide one viable method for Canadian governments to address this challenge. This study explores options to strengthen Canada’s organizational capacity for P3s, so that it may optimize the use of this procurement model to alleviate its worsening infrastructure conditions. Case study findings from the UK and Australia and synthesis of information from elite interviews identify a number of possible alternatives for evaluation. Broad policy recommendations include strengthening federal funding and institutional support, fostering a national P3 market and building public sector expertise.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".