MétaCan
Menu
Back to cohort
Record W2286050481

AN ANALYSIS OF DRINKING AND DRIVING BEHAVIORS IN THE US

2001· article· en· W2286050481 on OpenAlexaboutno aff
Patrick McCarthy

Bibliographic record

VenueSelected Proceedings of the 9th World Conference on Transport ResearchWorld Conference on Transport Research Society · 2001
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsnot available
Fundersnot available
KeywordsBinge drinkingMicrodata (statistics)Environmental healthAlcoholAlcohol consumptionInjury preventionDrunk drivingPoison controlConsumption (sociology)Suicide preventionHuman factors and ergonomicsPsychologyEconomicsMedicinePopulationChemistry
DOInot available

Abstract

fetched live from OpenAlex

Because of its implications for property damage, serious injury, and death, driving under the influence (DUI) of alcohol is a public health issue that has received considerable attention in the literature. Although research in this area is vast, the majority of work has focused either upon the demand for alcohol or upon the major highway consequence of combining alcohol consumption with motor vehicle operation, alcohol related crashes. Studies on the demand for alcohol typically estimate demand elasticities. A number of alcohol studies focus upon the drinking activities of youths found that youths' frequencies and intensities of beer and liquor drinking were price sensitive; price, however, was an insignificant determinant of wine consumption. Employing a microsample of 1,761 youths, it was found that minimum age laws and beer taxes have the greatest effects upon alcohol use. And from microdata collected in 1982 and 1989 on a representative sample of high school seniors before and after passage of the Federal Uniform Drinking Age (FUDAA) Act of 1984, it was found that youth frequencies and intensities of alcohol consumption were price sensitive but that their price sensitivities fell after passage of FUDAA. The paper describes binge drinking among college students and price elasticities differed by gender. Underage drinking and binge drinking by male students were generally price insensitive in comparison with females. And policies aimed at DUI activities among youths were beneficial in curbing college student drinking activities. Complementing these demand studies, the paper focused upon alcohol availability. It found that increases in alcohol availability increase the demand for alcohol; on the other hand, found little support for a positive relationship between consumption and availability. In a related study of alcohol advertising, it was found that the introduction of alcohol advertising in Saskatchewan had no effect on total alcohol or wine sales, although there was an offsetting effect on beer and distilled spirits sales. The other major strand of DUI research focuses upon highway safety and analyzes the effects that minimum age drinking laws, prices, alcohol availability, and other alcohol control policies have upon alcohol related highway crashes. There is a developing consensus in the literature that alcohol prices, and in particular beer prices, are efficacious in reducing highway crashes. The paper described how excise taxes have had a significant effect on fatality rates. In contrast to the effects of various alcohol control policies, mandatory sea belt use laws and beer taxes to be most effective in lowering driving under the influence fatalities. Alcohol price was a significant deterrent to heavy drinking by adults and youthful drinkers. The paper also reports on how a study found a significant beneficial effect of an increase in beer taxes on highway safety. However, in sharp contrast to these results, another study reports that neither alcohol prices nor beer taxes have a significant effect on highway safety.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.152
GPT teacher head0.418
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueSelected Proceedings of the 9th World Conference on Transport ResearchWorld Conference on Transport Research SocietySame topicAlcohol Consumption and Health EffectsFrench-language works237,207