Understanding Variance in Pilot Performance Ratings
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
Two studies were designed to investigate how pilots of different rank evaluate flight-deck performance. In each study, the pilots were asked to assess sets of three different videotaped scenarios featuring pilots in a simulator exhibiting poor, average, and good performance. Study 1, which included 92 airline pilots of differing rank, was aimed at comparing how individuals rate performance. The subjects used a standardized assessment form, which included six criteria, each having a 5-point rating scale. Analysis of the first study revealed that there was considerable variance in the performance ratings between flight examiners, captains, and first officers. The second study was designed to better understand the variance. Eighteen pilots (six flight examiners, six captains, and six first officers) working in pairs evaluated performances, in a modified think-aloud protocol. The results showed that there were good reasons for the observed variances. The results are discussed in relation to inter-rater reliability.
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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) | 0.010 | 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 it