PUBLIC ATTITUDES, EPIDEMIOLOGY AND CONSEQUENCES OF DRINKING AND DRIVING IN BRITISH COLUMBIA
Bibliographic record
Abstract
Injury is the ninth most common cause of premature death worldwide and the third most common cause of years lived with disability. Many early deaths are related to motor vehicle crashes (MVC's): each year, MVC's kill 1.2 million people (3,242 deaths/day) and injure or disable 20–50 million more. The Global Burden of Disease Study, conducted in the early 1990s, predicted that traffic-related injuries will become the third largest contributor to global death and disability by the year 2020. The identification of effective strategies for the prevention of traffic related injuries is of global health importance. The substantial effect of alcohol on road safety has long been recognized, and a variety of important initiatives to combat this problem have been introduced with some measurable success. Canadians have rated drinking and driving as one of the most important social issues facing them today, placing it ahead of other prominent issues, including health care, pollution, and the state of the economy. Two factors that have contributed strongly to motor vehicle injuries and fatalities in British Columbia (BC) and Canada are alcohol-impaired driving and failure to use seat belts. Drivers who operated motor vehicles after drinking were less likely to wear seat belts, and so they continue to be a major traffic safety concern. When compared to restrained occupants, unrestrained occupants were almost 5 times more likely to die (Odds Ratios (OR) 4.70), or be injured (OR 4.66). Fractures (OR 10.70, 95% confidence intervals [CI] 7.35–15.5), lacerations (OR 7.50, CI 5.55-10.15) bleeding (OR 7.14, CI 4.97–10.26) and concussions (OR 5.49, CI 2.71-11.12), were the more common types of injuries experienced by unrestrained occupants compared to the restrained occupants. Laws mandate the use of safety belts by motor vehicle occupants, and driving under the influence of alcohol is a generic term for a series of offences under the Canadian Criminal Code. Violation of Road Traffic Laws continues to be a serious ‘social problem’ and can often have fatal consequences as demonstrated in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".