Bibliographic record
Abstract
Buvik, K. (2013). How bartenders relate to intoxicated customers. International Journal of Alcohol and Drug Research, 2(2), 1-6. doi: 10.7895/ijadr.v2i2.120 (http://dx.doi.org/10.7895/ijadr.v2i2.120)Aims: In many studies, the extent of over-serving has been registered, but few attempts have been made to understand what happens in these situations when alcohol is ordered. The present study was designed to address two questions: How can we understand and explain why bartenders over-serve customers who are clearly intoxicated? What influences the interactions between bartenders and customers in situations in which alcohol is served?Design: Observation of 32 purchase attempts with pseudo-patrons, and in-depth interviews with seven bartenders. The bartenders interviewed were not those who were involved in the test purchasing.Findings: In the majority of cases, the pseudo-patrons were served without the bartender showing any sign of evaluating the customer’s level of intoxication. Three factors affect the bartenders’ interactions with intoxicated customers: a working situation not adapted for responsible serving; a drinking culture with a collective acceptance of intoxication; and opposition to the Alcohol Act, which is seen as too strict and ineptly enforced. Bartenders blamed their serving of intoxicated patrons on hectic working conditions as well as on wanting to maintain a good atmosphere in the bar and avoid conflicts. Observation at the premises showed a liberal drinking culture that legitimizes a high level of intoxication.Conclusions: As long as the customer appears pleasant and not confrontational, they can have another beer. Serving is the rule, and denial of service is the exception.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".