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Research and the alcohol industry

2003· letter· en· W1979266665 on OpenAlexaff
Gerhard Gmel, Jean‐Luc Heeb, Jürgen Rehm

Bibliographic record

VenueAddiction · 2003
Typeletter
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsAlcohol industryCompetition (biology)PopulationConsumption (sociology)Value (mathematics)MedicinePolitical scienceEconomicsBusinessAdvertisingEnvironmental healthSociologySocial science

Abstract

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Sir—On 1 July 1999 the spirits (liquor) market in Switzerland was reformed based on the World Trade Organization (WTO) agreement to eliminate unfair taxation on foreign beverages. The tax reform, in addition to increased competition, has resulted in a 30–50% decrease in price for foreign spirits. In a longitudinal individual-level study with baseline measurement 3 months before the tax reform and three follow-ups, the third follow-up being conducted 28 months after the tax reform, it could be shown that spirits consumption increased by about 40%. The increase in consumption was most marked in young people (Heeb et al. 2003; Kuo et al. 2003). In addition, purchases of spirits also increased, whereby purchases abroad decreased in favour of purchases in Switzerland (Heeb & Gmel 2003). In sum, the study replicated the common finding that alcoholic beverages were price-elastic. The main value of the study was that the effect could be established in an individual-level study with a pre–post design. The main fieldwork was funded by the Swiss Alcohol Board (PIs: Gerhard Gmel, Jean-Luc Heeb), with additional funds for analyses obtained from the National Institute on Alcohol Abuse and Alcoholism (NIAAA 1 R01 AA13346–01A1; PIs: Jürgen Rehm, Gerhard Gmel). Thus, the study design and analyses plan underwent one of the most competitive review process in the alcohol field. Descriptive findings of this study, targeted at a general population audience, were presented in a research report of the Swiss Institute for Prevention of Alcohol and Drug Problems (SIPA) in February 2003 (Heeb & Gmel 2003). Of course, we suspected that such findings may not be appreciated by the alcohol industry. However, we did not expect that the alcohol industry would receive support from scientists. The industry commissioned an expert opinion on this report from Professor Emeritus Reinhold Bergler, who wrote not as a private citizen, but under the affiliation of the Department of Psychology, University Bonn. Not unexpectedly, given the funding, the expert opinion views concluded that the study did not meet scientific criteria, and therefore no conclusions could be drawn with regard to taxation as a preventive measure. Different forms of taxation legislation, e.g. a special tax on alcopops, are currently under consideration by the Swiss government. The points raised in the expert opinion were unconvincing. Some of the misunderstandings could have been solved if Professor Bergler had contacted the principal investigators of the study for further clarification. His expert opinion was presented at a press conference on 27 May. No one involved in the study, or other representatives of the Swiss Institute for the Prevantion of Alcohol Problems (Lausanne) or the Addiction Research Institute (Zurich) were invited. In terms of criticism, three main points were raised: representativeness, effect size and attrition. To answer to these points briefly: representativeness was established by probability sampling methods and response rates exceeding the Swiss Health Surveys (Swiss Federal Statistical Office 1994, 1998). Effect size was actually as predetermined in the power calculation: the elasticity found was approximately −1, which is very close to the effect sizes reported in the literature (e.g. Österberg 1995). Finally, attrition was at the usual level for Swiss general population surveys and many efforts were made to conduct sensitivity analyses with imputed missing values as well as non-response and attrition analysis (Heeb & Gmel 2003; Kuo et al. 2003). In these analyses, the basic effects could be confirmed. Professor Bergler, the industry's selected expert, cannot be considered an expert in the alcohol field: we say that with respect, but our opinion may be confirmed, as can be inferred from either the publication list on his own homepage (http://www.psychologie.uni-bonn.de/sozial/staff/bergler/bergler.htm) or by using standard literature databases such as ETOH or Medline. We would have ignored this opinion if the industry had not quoted it repeatedly in order to discredit our research. This misinformation may result in delaying or even stopping changes in Swiss alcohol policies, and therefore result in increases of alcohol-related disease and mortality burden, which could otherwise be prevented. We believe that the story we report here is important for the integrity of science, standards in academia and the credibility of the drinks industry.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.110
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.354
Teacher spread0.269 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations7
Published2003
Admission routes1
Has abstractyes

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