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Record W2496188121

Public-Private Investment Models for Roadway Infrastructure

2014· article· en· W2496188121 on OpenAlexaboutno aff
Bob Farley, Nick Norboge

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPublic-Private Partnership Projects
Canadian institutionsnot available
Fundersnot available
KeywordsTransportation infrastructureLeverage (statistics)BusinessPublic–private partnershipContext (archaeology)General partnershipPublic infrastructureStatuteInvestment (military)Environmental planningTransport engineeringFinanceEngineeringPolitical scienceComputer scienceGeographyPolitics
DOInot available

Abstract

fetched live from OpenAlex

The goal of this report is to provide a balanced, objective survey assessment of the benefits and limitations of transportation public-private partnership (P3) projects around the U.S. and Canada and an analysis of their application in a Texas context. Specifically, this report reviews (1) history of P3s and their use, (2) P3 best practices from around the U.S., (3) necessary conditions for successful partnerships as well as impediments to success, (4) existing Texas statutes and administrative procedures that govern these types of projects, and (5) possible considerations to increase use for the future. While P3s can offer alternative methods that leverage existing transportation dollars, report authors recognize that P3s constitute only part of the solution to addressing Texas infrastructure challenges.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0060.007
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0250.002

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 head0.062
GPT teacher head0.243
Teacher spread0.181 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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