Bibliographic record
Abstract
Specialized legal literature dealing with different aspects of international air law is rare. The developments often overtake the existing writings and there is a continuous need not only for updating, but also for future-oriented thinking. There is a practical need for a compact, yet exhaustive, and easily comprehensible reference book or textbook that deals with the most general aspects of international air law, that also deals with the constitutional issues and law-making functions of the International Civil Aviation Organization (ICAO). This book fills the gap as it is a general treatise on the law of international civil aviation aimed at the needs of university students and educators, government authorities, airlines, practicing lawyers, journalists, international organizations, and the general public. This book is motivated by the author's 25 years of experience as international civil servant in the Secretariat of ICAO in Montreal, with his last eight years as Director of the Legal Bureau responsible for the legal work program of the organization. In equal measure, the inspiration for the content of this book came from the author's academic work as Director of the Institute of Air and Space Law of McGill University (1989-1998) and his role as professor of law at that Institute until 2006.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".