TECHNICAL NOTE No drinking and driving for 17 to 20-year-olds Recommendation in the Chief Medical Officer’s
Bibliographic record
Abstract
limit in the United Kingdom is 0.8 g/l, and is the same for all drivers. Many European countries have a limit of 0.5 g/l. The Chief Medical Officer has recommended a zero limit for younger drivers. Young people at risk Most young people drive responsibly. Some studies suggest that young people drink-drive less often than older drivers, and young drink-drivers may drink less alcohol than older drink-drivers, although important variables such as car ownership and detection levels can differ between age groups. However, alcohol has a more damaging effect on the safety of young and novice drivers. With or without alcohol, younger drivers have a higher risk of crashes than older drivers. With a blood alcohol concentration of 0.5 g/l their crash risk is six times greater than if they had not drunk at all. 1 Alcohol use increases the risk of a crash for young and novice drivers 2.5 times more than it increases the risk for older drivers. 2,3 The leading cause of death among 16 to 18-year-olds is transport accidents. 4 In the United Kingdom in 2005, 17 to 19-year-old car drivers had 1,080 drinkdrive accidents. 5 A THINK survey 6 in 2007 found that younger drivers were less likely to find driving after drinking two pints very unacceptable (36 % of 15 to 29-year-old drivers, and 47 % of drivers over 30 years old). International adoption and success • In Europe, 14 countries set the blood alcohol concentration limit for novice or young drivers at or less than 0.02 g/l, effectively a zero limit. • In Ontario, Canada, the blood alcohol concentration for novice drivers was reduced from 0.8 g/l to zero in 1995. This led to a 19 % reduction in crashes in which the driver was aged 16 to 19 years. 7 • Australian states with a blood alcohol concentration limit of zero for novice
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.251 | 0.208 |
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".