Teen Crashes Declined After Massachusetts Raised Penalties For Graduated Licensing Law Restricting Night Driving
Bibliographic record
Abstract
In 2007, as part of the Massachusetts graduated driver-licensing program designed to allow junior operators (ages 16½-17 years) to gain experience before receiving full licensure, stringent penalties were introduced for violating a law prohibiting unsupervised driving at night; driver education, including drowsy driving education, became mandatory; and other new restrictions and penalties began. We evaluated the impact of these changes on police-reported vehicle crash records for one year before and five years after the law's implementation in drivers ages 16-17, inclusive, and two comparison groups. We found that crash rates for the youngest drivers fell 18.6 percent, from 16.24 to 13.22 per 100 licensed drivers. For drivers ages 18-19 the rates fell by 6.7 percent (from 9.59 to 8.95 per 100 drivers), and for those ages 20 and older, the rate remained relatively constant. The incidence rate ratio for drivers ages 16-17 relative to those ages 20 and older decreased 19.1 percent for all crashes, 39.8 percent for crashes causing a fatal or incapacitating injury, and 28.8 percent for night crashes. Other states should consider implementing strict penalties for violating graduated driver-licensing laws, including restrictions on unsupervised night driving, to reduce the risk of sleep-related crashes in young people.
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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 | 0.000 | 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) | 0.000 | 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".