Assessing the risks, cost and benefits of Australian aviation security measures
Bibliographic record
Abstract
The Australian government Office of Best Practice Regulation has recommended the use of cost-benefit assessment for all proposed federal regulations. Since 9/11 government agencies in Australia, United States, Canada, Europe and elsewhere have devoted much effort and expenditure to attempt to ensure that a 9/11 type attack involving hijacked aircraft is not repeated. This effort has come at considerable cost, running in excess of US$6 billion per year for the United States Transportation Security Administration (TSA) alone. In particular, significant expenditure has been dedicated to two aviation security measures aimed at preventing terrorists from hijacking and crashing an aircraft into buildings and other infrastructure; (i) Hardened cockpit doors and (ii) Air Security Officer (ASO) program (air marshals).These two security measures cost the Australian taxpayers and the airlines nearly $60 million per year. This paper seeks to discover whether these new aviation security measures are cost-effective. The preliminary cost-benefit analyses considers the effectiveness of security measures, their cost and expected lives saved as a result of such expenditure. An assessment of increased expenditure on the Air Security Officer (air marshals) program since 2001 suggests that the annual cost is $157.2 million per life saved. This is greatly in excess of the regulatory safety goal of $1-$10 million per life saved. As such, the ASO program seems to fail a cost-benefit analysis. In contrast, hardening of cockpit doors has an estimated annual cost of only $700,00 per life saved, suggesting that this strategy is a much more cost-effective security measure.
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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 | 0.000 | 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 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".