THE VALUE OF THE RARF FREEWAY SYSTEM: A CORPORATE-STYLE FINANCIAL ANALYSIS
Bibliographic record
Abstract
This report uses foundation and format developed in Phase I of SPR 475 - Value of Arizona's State Highway System: A Corporate-Style Financial Analysis, report number FHWA-AZ-99-475(1) - and adapts it to measure the financial performance of the Maricopa County freeways funded by the Regional Area Road Fund (RARF). The basic findings of this research can be summarized as follows: Under the assumptions of corporate-style accounting, the RARF freeway system has operated at a substantial loss over the past 12 years; These losses are projected to continue through the Maricopa Association of Governments system life cycle build-out in 2007; The average returns earned by the RARF Freeway System over the last five years lag those of other transportation and capital-intensive industries; The value of the regional freeway system exceeds 30 cents per vehicle mile of travel; Revenues generated by users of the RARF freeway system have averaged less than 4 cents per mile of travel; Highway user fees could be increased without significantly reducing use of the roadways; and An electronic tolling system would be the most efficient means of ensuring that highway users pay fees commensurate with their use of the highway system, with the RARF Freeway System being the most effective part of the state highway system on which to implement such a program.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".