What was wrong with the toll highway concessions in the Madrid Metropolitan Area?
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.
Bibliographic record
Abstract
Highway concessions are becoming quite popular all around the world as a means to promote private participation in the management and financing of public infrastructure. The congestion problems caused by the limited capacity of the road infrastructure networks in many metropolitan areas are prompting public authorities to adopt the concession approach to improve highway capacity, while at the same time implementing a congestion pricing approach. This paper describes and assesses the case study of a toll highway concession program, recently implemented in the city of Madrid, to build four radial toll highways intended to reduce congestion and at the same time to raise revenues to fund the new infrastructure. The concessions, which started their operations in 2003 and 2004, have not worked as well as expected. There are several reasons for this. The most important one is that they managed to capture only a small share of the traffic in the corridor. This has caused serious financial problems to the concessionaires, who are now on the verge of bankruptcy. This paper analyses both the reasons behind the government’s adoption of the concession approach, and the reasons why this approach ultimately proved unsuccessful. On the basis of the results of this case study, we offer a set of recommendations for policy makers when considering the use of toll highway concession contracts in metropolitan areas
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it