Awareness beyond the desktop: exploring attention and distraction with a projected peripheral-vision display
Bibliographic record
Abstract
The initiation of interaction in face-to-face settings is often a gradual negotiation process that takes place in a rich context of awareness and social signals. This gradual approach to interaction is missing from most online messaging systems, however, and users often have no idea when others are paying attention to them or when they are about to be interrupted. One reason for this limitation is that few systems have considered the role of peripheral perception in attracting and directing interpersonal attention in face-to-face interaction. We believed that a display exploiting people's peripheral vision could capitalize on natural human attention-management behavior. To test the value of this technique, we compared a peripheral-vision awareness display with an on-screen IM-style system. We expected that people would notice more information from the larger peripheral display, which they did. Moreover, they did so while attending less often to the peripheral display. Our study suggests that peripheral-vision awareness displays may be able to improve attention and awareness management for distributed groups.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".