Comparative study of civil aviation de-licensing regimes in New Zealand, Australia and Canada
Bibliographic record
Abstract
This paper looks at the civil aviation law for New Zealand, Australia, the USA and Canada in regards to the ‘de-licensing’ of participants in the aviation system. The comparative analysis is on each country’s ability to take administrative action against an aviation participant on an ‘on notice’ basis and, in cases where there is an imminent threat to aviation safety, on a ‘without notice’ basis. Issues looked at include:\n\n(a) The process the regulator must adhere to in bringing administrative action.\n(b) The appeal or review rights available to the aviation participant.\n(c) The availability of a stay to the aviation participant while he or she waits a full hearing.\n(d) The availability of a specialist tribunal with aviation expertise to hear an appeal.\n\nThe issues are examined in order to determine what, if any, improvements could be made to the New Zealand system. The paper concludes that the New Zealand system could be improved by providing for a more streamlined appeal or review process; a unified transport tribunal dealing with land transport, maritime and civil cases and an ability, in limited circumstances, for the Director's decision to be stayed pending a full hearing.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".