Komparace letecké legislativy v oblasti licencování leteckého personálu v EU, USA a Kanadě
Bibliographic record
Abstract
This article is focused on comparison and analysis of the aviation legislation governing the licensing of aviation personnel in the European Union, the United States of America, and Canada. The goal is to compare the differences in the legislative framework for aviation personnel licensing and the potential cross-border transfer and validation of licenses in between these regions. Furthermore, this work examines the implementation of international standards set by the International Civil Aviation Organization (ICAO) and the role of national and supranational organizations, including EASA, FAA, and Transport Canada. The European Union Aviation Safety Agency (EASA) oversees the standardization of legislation among EU member states. One of the many responsibilities of the Federal Aviation Administration (FAA) includes licensing aviation personnel in the United States of America. In Canada, matters of aviation legislative issues, including licensing of aviation personnel, are managed by Transport Canada Civil Aviation (TCCA). Despite the existence of a requirement for international unification of aviation personnel licensing, differences can be found between individual national legislations, and therefore, in the case of foreign license validation, fulfillment of specific requirements is necessary for their international transfer and recognition.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".