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Record W1973631090 · doi:10.15288/jsad.2009.70.126

Effects of Sunday Sales Restrictions on Overall and Day-Specific Alcohol Consumption: Evidence From Canada

2009· article· en· W1973631090 on OpenAlexaboutno aff
Christopher S. Carpenter, Daniel P. Eisenberg

Bibliographic record

VenueJournal of Studies on Alcohol and Drugs · 2009
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersCenter for Substance Abuse Prevention
KeywordsConsumption (sociology)LiberalizationNames of the days of the weekAlcohol consumptionPopulationPoison controlAlcoholEnvironmental healthDemographyMedicineDemographic economicsBusinessEconomics

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to estimate the effect of Sunday alcohol-sales policies on day-specific and overall alcohol consumption. METHOD: Individual-level data on overall and day-specific alcohol consumption from Canada's National Population Health Surveys, 1994-1999, were linked to province-level policy variation in whether a Sunday sales restriction was present. We compared individuals in provinces with sales restrictions with those in provinces without such restrictions, and we estimated models of day-specific and overall alcohol consumption. We used a standard cross-section model as well as a quasi-experimental approach that relied on Ontario's liberalization of Sunday sales in 1997. RESULTS: Sunday sales were associated with a significant increase in drinking on Sundays of 7% to 15%. We found evidence of substitution away from drinking on Saturdays and no evidence for increases in overall drinking. CONCLUSIONS: Our results suggest that repealing Sunday sales prohibitions is unlikely to result in increased overall alcohol consumption, although such liberalization may change the within-week distribution.

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)0.003
metaresearch head score (Gemma)0.017
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 score0.022
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.319
Teacher spread0.263 · 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

Citations45
Published2009
Admission routes1
Has abstractyes

Explore more

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