Airport level of service perceptions before and after September 11: a neural network analysis
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
Physical infrastructure is constructed to provide services to it users. The perceptions of users regarding the level of service are not necessarily constant, however, making it necessary to adapt both the infrastructure and its attending services to adjust to new user demands. The tragic events of September 11, 2001 had just such a disruptive effect on the perception of service levels at airports. This paper uses neural network analysis to examine passenger survey data before and after the September 11 th attacks to identify shifts in level of service perceptions at Ottawa Airport. The analysis suggests a significant change occurred in the components that comprised passenger satisfaction levels, even though the overall level of satisfaction was largely unaffected. The results have clear implications for airport authorities in terms of maintaining or improving service provision in the presence of continuing security concerns.
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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 | 0.001 |
| 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) | 0.006 | 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