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Record W2804734141 · doi:10.1061/9780784481295.014

The USA PPP Payment Mechanisms: A Comparison to the Canadian PPP Systems

2018· article· en· W2804734141 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueConstruction Research Congress 2018 · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentBusinessTollPayment service providerActuarial scienceFinance

Abstract

fetched live from OpenAlex

Over the years, PPPs in the USA have used different types of payments to compensate project developers. In the past decades, the dominant type was toll payment. Availability payments started to gain more popularity with performance-based PPP contracts. Internationally, some other payment types are also used in PPPs, such as operation and maintenance payment, safety payment, satisfaction payment, and end of term payment. A payment mechanism is a package that includes a set of payment type(s), performance measures, performance specifications, and penalties for not meeting the specifications. Since PPP payment mechanisms, other than toll payments, is new in the USA, it is not clear whether payment mechanisms as used in the USA projects would be similar to those used in the PPP international market regarding the payment types, payment structure, performance measures and specifications, penalties, and deduction schemes. This research investigated the payment mechanisms in transportation PPP projects in the USA and Canada. Comparative and content analyses of project agreements are used as research methods. The findings show that PPP projects in the USA tend to have payment mechanisms of fewer payment types, less sophisticated payment calculations, and less complex deduction schemes. Public agencies would use the outcome of this research to revisit and improve the design of payment mechanisms of their PPP projects.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.692
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.007

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.

Opus teacher head0.120
GPT teacher head0.363
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it