A mystery-shopping study to test enforcement of minimum legal purchasing age in Lithuania in 2022
Bibliographic record
Abstract
BACKGROUND: According to the Lithuanian law to prevent the sale of alcohol to customers below the legal minimum purchasing age of 20 years, young adults below 25 years must be asked to show an age-verification document when purchasing alcohol. The aim of this study was to assess whether off-premise outlets comply with the law. METHODS: In 2022, mystery-shopping study was carried out in three consecutive phases: (i) in a representative sample (n = 239) of off-premise alcohol outlets covering all Lithuanian district centres, (ii) after lifting the requirement to wear a mask and (iii) after warning the outlets that a mystery-shopping study was ongoing. Phases 2 and 3 were held in two cities. The mystery shopping involved attempts by young, but legally eligible customers to purchase alcohol. Across the three study phases, we compared compliance with the law by measuring overall success of purchase attempts and included situational characteristics (working day or weekend), time of day and number of customers in line as an additional predictor. RESULTS: Out of 239 attempts to purchase alcohol from off-premise outlets in the main phase of the study, 107 (or 44.8%) were considered to be successful (visits in which staff were willing to sell alcohol). There was a significantly higher chance of success to purchase alcohol with no ID request if a mystery shopper was the only customer in a queue and on weekends. CONCLUSIONS: The results indicate an insufficient level of age-verification control in Lithuania, and that additional action is needed to increase compliance.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".