Talking on the Phone While Driving: The Effects of Divided Attention on Change Detection
Bibliographic record
Abstract
The proposed study focuses on change detection in a driving scenario, with the concurrent task of talking on a cell phone. The purpose of this study is to investigate how attention divided between talking on a hands-free device and driving induces change blindness for a visual stimulus. Eighty participants will partake in a virtual drive simulation from a driver’s viewpoint. Participants will engage with a dynamic driving scene while either concurrently maintaining a conversation on a hands-free device or concentrating solely on the driving task. The scene will be intermittently interrupted by a flicker, in which one object, the target stimuli in the scene, will change. Participants will be asked to report the location of the changed target and its schematic relevance to a driving scene. Longer gaze fixations on the target will be indicative of change detection, and shorter fixations will represent change blindness. Past research has shown that individuals are more likely to detect items with semantic relevance to a driving scene, as well as changes that are centrally located. It is expected that participants whose attention is divided between talking on a cell phone and driving will experience impaired change detection. Participants are expected to exhibit change blindness for semantically irrelevant targets in central regions, which is exacerbated for semantically irrelevant targets in marginal areas.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".