Qualitative analysis of UK women’s attitudes to calorie-based alcohol marketing and alcohol calorie labelling
Bibliographic record
Abstract
Mandatory standardized nutritional information on alcoholic drinks such as energy, or calorie labelling, is a population-level public health measure aimed at addressing obesity and alcohol consumption. In the UK, such measures are not a statutory requirement, but some alcohol brands do include references to calories on their products and in their marketing materials, as a marketing strategy to encourage sales and consumption. This article presents findings of semi-structured individual (N = 43) and group (N = 9) interviews with 78 women living in the UK that aimed to gain insight into their attitudes towards calorie-based alcohol brand marketing, and alcohol calorie labelling (ACL) as a health policy. Three themes are presented that outline how women rejected calorie marketing and labelling; the potential positive and unintended impact on alcohol consumption and dietary/eating practices; and how views on calorie labelling were intertwined with women's attitudes towards marketing that draws on calorie messaging. A feminist anti-diet discourse, as well as a discourse of pleasure through alcohol consumption, was at play in women's accounts, which may limit the intended aims of ACLs. It is concluded that ACLs should be considered within the wider commercial context of alcohol marketing that draws on calories to promote sales and consumption, consideration of the gendered factors that may lead some to reject ACLs as a health policy, and the potential for unintended consequences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".