Airport privatisation across the Atlantic: Contrasting examples of success and failure, aspiration and reticence in the USA and UK
Bibliographic record
Abstract
For many reasons, partly financial, partly political and partly historic, the privatisation of airports in the USA (and Canada) has never really ‘taken off’. Even taking into account the recently concluded transaction to lease the major airport in Puerto Rico, the track record of deals since the Airport Privatisation Pilot Program was instigated in 1996 is abysmal. In contrast, the UK embraced airport privatisation to such a degree since the mid 1980s that it is now one of the most privatised countries in the world in terms of airport infrastructure. In the UK, political factors were very much at the forefront of this tendency. Only one airport group held out against the movement, but it too has now succumbed to the tide and, belatedly, has both peculiarly and innovatively concocted a scheme by which at one and the same time it will sell part of its own equity to a strategic partner in order to invest in another airport on a ‘no win-no fee’ basis to the partner. This paper seeks to examine the underlying reasons behind this dichotomy while posing the question, ‘has airport privatisation to date really been of benefit to the consumer?’
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".