Towards Mitigating Teenagers’ Distracted Driving Behaviors
Bibliographic record
Abstract
Distraction contributes significantly to teens’ crash risks. Previous studies show that feedback can help mitigate distraction among young and adult drivers; however, the type of feedback that is effective for teenagers remains unexamined. This paper investigates whether real-time and post-drive feedback can mitigate teens’ driver distraction and reports preliminary findings from an ongoing simulator study. Data reported was collected in a between-subjects experiment with three conditions: real-time (n= 8), post-drive (n= 8), and no feedback (n= 9). Real-time feedback was provided as auditory warnings when teens had long offroad glances (>2 sec). Post-drive feedback was an end-of-trip report on teens’ off-road glances and driving performance provided on an in-vehicle display. Compared to no feedback, real-time feedback resulted in significantly smaller number of long off-road glances (>2 sec), smaller average duration of off-road glances, and smaller standard deviation of lane position. The effects observed for post-drive feedback were relatively minor.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".