Bibliographic record
Abstract
The formation of airline alliances has been a distinctive feature of the airline business at the threshold of the new millennium. This is due to the framework of Bilateral Air Transport Agreements, which condition the grant of traffic rights to substantial ownership and effective control being vested in nationals of one of the contracting parties. Further regulatory aspects pertaining to airline alliances include competition law review, traffic rights, and slot allocation. This thesis seeks to elucidate how Star had to adapt its strategic choices to this framework. The outcome will be that in particular the lack of regulatory convergence in competition law matters constitutes a hindrance to a global alliance such as Star. The issue of ownership and control might represent a further obstacle to an alliance intending to rely on mergers or major share holding, an ambition that Star has not nourished so far. Open Skies agreements in force between the U.S., Canada, and several member states of the European Union give alliances full commercial opportunities, unhindered by restrictive capacity or approval of fares provisions. The principles as regards slot allocation, on the other hand, have enabled alliances to build up their hubs as fortresses. The issues of competition law, and ownership and control illustrate that it has become increasingly insufficient to rely on a merely bilateral approach to global problems. Eventually, satisfactory solutions may only be achieved on a multilateral level. The onus thus is on aviation regulators to come up with a more suitable framework for aviation in the next century. Multilateralism, however, might turn out to herald the end to the alliance phenomenon. Once the bilateral strait jacket put aside, the aviation industry will consolidate like any other industry: by mergers, that is.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".