Bibliographic record
Abstract
The final investigation report for the 1998 Swissair Flight 111 collision was released by the Transportation Safety Board of Canada in March 2003. This paper analyzes the human factors of the accident involving the captain's and first officer's use of checklists and their cockpit communication. A case study is presented that analyzes the use of checklists of Swissair 111 and their use in the aviation industry at that time. After reviewing and discussing past research on cockpit communication, publicly available information from the Swissair 111 cockpit voice recorder (CVR) is analyzed. The flight crew's communication is placed into some broad categories of linguistically-oriented aviation communications research. The author recommends the full Swissair 111 CVR transcript be released to leaders in the field of aviation psycholinguistics for further research. This transcript could be used for study of real-time aircraft emergency cockpit communication, possibly resulting in improved safety recommendations and pilot training. Findings suggest that although checklists did not play a role in the outcome of Swissair 111, conflicts did arise between two of the checklists. This suggests that the aviation industry should standardize and rationalize checklists and checklist procedures.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".