A different kind of partnership: an infrastructure performance stock exchange
Bibliographic record
Abstract
Typically, public–private partnerships are constrained to be ‘mega’ construction projects and long-term arrangements. This paper introduces a practical mechanism for a novel public–private partnership modelled on the concepts of market trading (i.e. stock exchange). The ultimate mega project is the management of an entire infrastructure asset network by a government agency (federal, provincial, local, etc.). Hundreds of billions of dollars are spent each year in North America on the upkeep of public infrastructure (roads, underground, buildings, parks, etc.). Yet, according to current projections, this is still far short of the funding that is required to achieve acceptable levels of performance or service. A transparent, evidence-based and auditable process for deriving a universal infrastructure asset performance stock measure is introduced. Rather than being based on asset age, as the current ‘old infrastructure order’ is, the ‘new infrastructure order’ of asset management is based on the principles of reliability (risk) engineering as applied to corporate information.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".