Can progress in reducing alcohol-impaired driving fatalities be resumed? Results of a workshop sponsored by the Transportation Research Board, Alcohol, Other Drugs, and Transportation Committee (ANB50)
Bibliographic record
Abstract
Objective: Despite successes in the 1980s and early 1990s, progress in reducing impaired driving fatalities in the United States has stagnated in recent years. Since 1997, the percentage of drivers involved in fatal crashes with illegal blood alcohol concentration (BAC) levels has remained at approximately 20 to 22%. Many experts believe that public complacency, competing social and public health issues, and the lack of political fortitude have all contributed to this stagnation. The number of alcohol-related crashes, injuries, and fatalities is still unacceptable, and most are preventable. The public needs to be aware that the problem presented by drinking drivers has not been solved. Political leaders need guidance on which measures will affect the problem, and stakeholders need to be motivated once again to implement effective strategies. Methods: The National Academy of Sciences (NAS) Transportation Research Board (TRB), Alcohol, Other Drugs, and Transportation Committee (ANB50) sponsored a workshop held at the NAS facility in Woods Hole, Massachusetts, on August 24–25, 2015, to discuss the lack of progress in reducing impaired driving and to make recommendations for future progress. A total of 26 experts in research and policy related to alcohol-impaired driving participated in the workshop. The workshop began by examining the static situation in the rate of alcohol-impaired driving fatal crashes to determine what factors may be inhibiting further progress. The workshop then discussed 8 effective strategies that have not been fully implemented in the United States. Workshop participants (16 of the 26) rated their top 3 strategies. Results: 3 strategies received the most support: 1. Impose administrative sanctions for drivers with BACs = 0.05 to 0.08 g/dL.2. Require alcohol ignition interlocks for all alcohol-impaired driving offenders.3. Increase the frequency of sobriety checkpoints, including enacting legislation to allow them in the 11 states that currently prohibit them. Impose administrative sanctions for drivers with BACs = 0.05 to 0.08 g/dL. Require alcohol ignition interlocks for all alcohol-impaired driving offenders. Increase the frequency of sobriety checkpoints, including enacting legislation to allow them in the 11 states that currently prohibit them. 5 other important strategies included the following: (1) increase alcohol taxes to raise the price and reduce alcohol consumption; (2) reengage the public and raise the priority of impaired driving; (3) lower the illegal per se BAC limit to 0.05 for a criminal offense; (4) develop and implement in-vehicle alcohol detection systems; and (5) expand the use of screening and brief interventions in medical facilities. Conclusions: Each of these strategies is proven to be effective, yet all are substantially underutilized. Each is used in some jurisdictions in the United States or Canada, but none is used extensively. Any one of the 3 strategies implemented on a widespread basis would decrease impaired driving crashes, injuries, and fatalities. Based on the research, all 3 together would have a substantial impact on the problem.
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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 | 0.051 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".