Bibliographic record
Abstract
AIMS: To evaluate the effects of changes in aggregate alcohol consumption on overall fatal accidents, motor vehicle accidents, fatal falling accidents and drowning accidents in Canadian provinces after 1950. DESIGN: Time-series analysis of annual mortality rates (15-69 years) in relation to per capita alcohol consumption, utilising the Box-Jenkins technique. All series were differenced to remove long-term trends. MEASUREMENTS: Gender-specific and age-adjusted mortality rates for the age group 15-69 years were calculated on the basis of mortality data for 5-year age groups, using a standard population. Data on per capita alcohol consumption was converted to consumption per inhabitant 15 years and older. In the analysis of motor vehicle accidents, the number of motor vehicles was used as a control variable. FINDINGS: Statistically significant associations between alcohol consumption and overall fatal accident rates were uncovered in all provinces for males, and in all provinces except Ontario for females. For Canada at large, an increase in per capita alcohol consumption of 1 litre was accompanied by an increase in accident mortality of 5.9 among males and 1.9 among females per 100,000 inhabitants. Among males there was a significant association with alcohol for both falling accidents, motor vehicle accident and other accidents, but the association was insignificant for drowning accidents. Among females, the association with falling accidents and other accidents was significant. CONCLUSION: Changes in alcohol consumption have had substantial effects on most of the main types of fatal accidents in Canada during the second half of the 20th century. The size of the association is comparable to the one previously reported from Northern Europe.
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 | 0.000 | 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".