[Commentary] ALCOHOL AND SPONSORSHIP IN SPORT: SOME MUCH‐NEEDED EVIDENCE IN AN IDEOLOGICAL DISCUSSION
Bibliographic record
Abstract
First, we would like to congratulate O'Brien & Kypri 1 for their empirical analysis and findings of the association between alcohol industry sponsorship in sport, level and patterns of alcohol consumption of athletes and alcohol-related harm. Considering that the banning of advertisement and sponsorship from the alcohol industry is one of the most symbolic bones of contention between the public health community and the alcohol industry, it is surprising what little is known about the actual effects of alcohol and other sponsorship in sport. The paper by O'Brien & Kypri 1 is an initial step, but it is important that the more ideological points in this debate make place for more evidence-based argumentation. When Babor et al.2 conducted their overview on the effectiveness of alcohol policies they left a question-mark on the impact of alcohol control measures for advertisement and sponsorship, in part because the effects were not well known. Since then there have been a number of studies, summarized by Peter Anderson and colleagues (see the ELSA report: 3, which have clearly shown the impact of alcohol advertisement on use by adolescents. However, the impact of sponsorship by the alcohol industry on the people participating and attending sponsored events has not been studied widely, which leaves a major knowledge gap in instituting policy recommendations. As a result, such recommendations have often been based on the reasoning and the evidence of tobacco control measures 4. O'Brien & Kypri 1 have two important implications which we would like to consider further. First, they demonstrate that sponsorship and advertising seem to have similar results, in that consumption is increased. Secondly, by placing their research in a sports context, the authors highlight the role and importance of this part of our culture. The first point is a major blow to the arguments of those who claim that sponsorship is not a marketing method similar to advertisement; that it is not implemented based on the same principles and does not aim at similar gains or effects, i.e. brand loyalty and consumption increases. If the form and effects of sponsorship are similar to the more traditional ones of advertisement, the question arises as to why is alcohol industry sponsorship treated and regulated differently from advertising in so many countries? Sports sponsorship was, to a large degree, launched by tobacco and alcohol executives in order to overcome growing marketing constraints placed upon them with respect to traditional advertisements 5. This would certainly include policy reforms implemented to limit the public health problems to which their products contributed. Sport is universal. It is has existed throughout civilization and is prominent throughout our lives, whether in our youth as a rite of passage, a regular pastime or an obsession. Similar things can be said of alcohol. Along with countless ‘universals’, both are also multi-billion-dollar industries. However, a major difference between the two is that the alcohol industry has something of an ‘image’ problem; namely, the fact that its product contributes to multiple diseases, and overall to a significant portion of the global burden of disease 6 as well as to social problems. On the contrary, sport still has a more positive image, although doping has surely damaged part of it. Thus, associating with sports is enticing for the alcohol industry, trying to achieve credibility and cultural capital. At this stage, we do not know whether these mechanisms are actually working as postulated. However, thanks to O'Brien & Kypri 1, we know that there is an association between sponsorship and problem drinking. The next steps are to explore the causality of such relations, as well as the pathways that lead from sponsorship to drinking behaviour. Such exploration is not only necessary for assessing the effects of sponsorship in sports, but for all new forms of advertising such as internet marketing techniques or ‘street-level’ guerilla marketing. Any potential policy recommendations should be based on empirical evidence on pathways and effects. Empirical evidence should be based on postulated theoretical relationships and pathways. In that sense, evidence can be transferred from tobacco control to alcohol for the same causal pathways. If the same pathways are involved, there will be no good argument as to why the effects of sport sponsorship by the alcohol industry should be different from those of the tobacco industry. However, each different pathway has to be established and analysed empirically. Hopefully, the next years will bring more such careful analyses in relevant areas. The first author has participated in scientific meetings organized or sponsored by the alcohol industry and received financial support for this participation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".