<scp>Recent Developments in the Aviation Insurance Industry</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The aviation industry has been hard hit in recent years. While there are numerous factors that have contributed to the industry's dilemma, rising and volatile insurance premiums—particularly after the events of 9/11—have posed a particular problem for many airline managers. Despite a general trend for accident rates involving commercial passenger airplanes to decrease as aviation technology has advanced over the years and airplanes have become safer, the aviation insurance market has been far from stable. This article provides an overview of how the aviation insurance industry works and how it has changed in recent years. We take a look at how the risk is spread between insurers, how insurers treat deliberate acts of violence, and lastly, how insurers price the risk. Our article shows that the aviation insurance market has undergone considerable changes in recent years and that it has adjusted to the post‐9/11 aviation insurance realities being reasonably ready to handle events of an even more catastrophic magnitude.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it