Alcohol and Driving: The Development of Law Enforcement Countermeasures in Canada
Bibliographic record
Abstract
SummaryIn 1969, the Canadian Parliament took two significant steps against DUI by adopting a “per se” law making it an offense to drive with a blood alcohol concentration (BAC) greater than 80 mg of alcohol in 100 milliliters of blood and also making it an offense to refuse to provide a breath sample on demand. Since these 1969 provisions, addition legislative changes have been made to deal with specific DUI-related issues. In 1985, legislation was enacted to address the taking of blood samples when breath sampling is impractical or impossible. In 2008, the so-called “two beer” defense was significantly impeded by new limitations placed on the “evidence to the contrary” provision. The impact of this provision is still being assessed. New defenses for DUI then emerged based on attacks on the breath-test instrument itself and its manner of operation. Making DUI legislation part of the Criminal Code of Canada (CCC) resulted in making the basic legislation against DUI uniform across the country, and it makes the implications for violators very serious. Because the consequences for a convicted driver can be so serious, it is essential that the investigative process, including the breath test, be conducted according to the highest standards. This means that all investigative steps should be properly performed at the police station, not at the roadside or back of a police vehicle. In fact the practice of transporting an arrested driver to a police station for testing may be one of the more significant deterrents for potential offenders. Although existing legislation has been important in reducing the number of deaths and serious injuries from DUI, accidents caused by DUI remain unacceptably high in Canada. 14 references
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 | 0.001 | 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".