Improving the Management of Interruption through the Working Awareness Interruption Tool: WAIT
Bibliographic record
Abstract
Interruptions in time-critical, dynamic and collaborative environments, such as Air Traffic Control (ATC), can provide valuable, task-relevant information. However, they also negatively impact task performance by distracting the operator from on-going tasks and consuming “attention resources”. It is hypothesized that operators in these environments could better manage when interruptions occur if there were indications of the availability of a collaborator and the priority of an interruption. The Working Awareness Interruption Tool (WAIT) is being developed to support more efficient and appropriate interruption timing in the context of complex, real-time, distributed, human operator interactions. Prototypes for application in operational ATC displays are presented as well as techniques used to develop the design requirements. Feedback on the initial prototypes was solicited through a Participatory Design (PD) interview process with air traffic controllers. The implications of the findings for the feasibility of an interruption awareness tool in real ATC environments are discussed.
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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 | 0.003 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".