THE RELATIONSHIP BETWEEN ALCOHOL USE AND MORTALITY RATES FROM INJURIES: A COMPARISON OF MEASURES
Bibliographic record
Abstract
Per capita consumption of alcohol has traditionally been considered to be the leading indicator of population levels of alcohol problems. However, some recent research suggests that this relationship may be weakening, and that drinking pattern measures may be preferable to per capita consumption as problem-level indicators. We compared the ability of per capita alcohol consumption and survey-based measures of alcohol use to predict deaths from injuries in Ontario, Canada, for the period 1977-1996. Per capita consumption and percentage of daily drinkers were significantly related to injury mortality, but percentage of drinkers and percentage of episodic heavy drinkers (those who drank five or more drinks on a drinking occasion) were not. Of the measures we examined, per capita consumption was the strongest indicator of mortality rates from injuries. However, the survey-derived measure of percentage of daily drinkers was similar to per capita consumption in ability to predict problem levels.
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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 | 0.001 | 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".