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Record W2016016998 · doi:10.1177/009145091203900403

A Comparison of Private and Government-Controlled Liquor Stores in British Columbia

2012· article· en· W2016016998 on OpenAlexaboutno aff
Scott Macdonald, Andrew J. Treno, Tim Stockwell, Gina Martin, Jinhui Zhao, Bill Ponicki, Alissa Greer

Bibliographic record

VenueContemporary Drug Problems · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)PremiseBusinessMarketingAdvertising

Abstract

fetched live from OpenAlex

British Columbia (BC), Canada, has unique regulations for sales of alcohol in off-premise establishments where both government (n = 199) and privately controlled stores (n = 977) sell all types of off-premise alcoholic beverages. The purpose of this study is to compare the different marketing approaches of government and private stores and examine how their sales vary in relation to demographic characteristics within the regions that they operate. Data was collected for 89 geographic areas of BC from the following sources: a survey of BC private stores, BC demographic statistics, and sales records for different types of alcoholic beverages from private and government stores. Private stores had higher average prices, longer hours of operation, and were more likely to refrigerate beverages than government stores. Also, types of beverage sold differed between government and private stores depending on the demographic characteristics of the regions being served.

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)0.002
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 score0.027
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.236
Teacher spread0.210 · 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
Published2012
Admission routes1
Has abstractyes

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