Highway Public-Private Partnerships: Securing Potential Benefits and Protecting the Public Interest Could Result from More Rigorous Up-front Analysis
Bibliographic record
Abstract
Testimony issued by the Government Accountability Office with an abstract that begins "The private sector is increasingly involved in financing and operating highway facilities under long-term concession agreements. In some cases, this involves new facilities; in other cases, firms operate and maintain an existing facility for a period of time in exchange for an up-front payment to the public sector and the right to collect tolls over the term of the agreement. In February 2008 GAO reported on (1) the benefits, costs, and trade-offs of highway public-private partnerships; (2) how public officials have identified and acted to protect the public interest in these arrangements; and (3) the federal role in highway public-private partnerships and potential changes in this role. The Senate Finance Committee asked GAO to testify on this report and to highlight its discussion of tax issues. GAO reviewed the experience of projects in the U.S. (including the Chicago Skyway and Indiana Toll Road agreements), Australia, Canada, and Spain."
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 | 0.031 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 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".