Air Traffic Management under Stress: The Performance of Air Navigation Providers in Canada, Britain, and the United States
Bibliographic record
Abstract
This paper describes how Air Traffic Management (ATM) reform efforts in Canada, Britain, and the United States have similar roots, but they all have taken quite distinct restructuring paths. All three countries have been subject to dramatic changes in the airline industry in recent years, especially since 2001. Each air traffic organization was forced to respond in different ways, shaped by the context in which it was formed, the extensive use of debt finance, and the ability (or lack thereof) to manage costs and revenues in a declining environment. The stakeholder model of NAV Canada appeared to be the most flexible in its capacity to respond to industry conditions. The financial structure and regulated industry position of NATS made it more difficult to adjust, but the subsequent restructuring appears to have dealt with many of these problems. Unlike its counterparts, the United States Federal Aviation Administration (FAA) managed the decline with the least change. While the ability to drawn on the government budget in time of crisis was critical to FAA. However, as industry conditions stabilized and growth resumed, both NAV Canada and National Air Traffic Services (NATS) appear to have more sustainable business models and organizational structures to meet the challenges of air traffic management in coming years.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".