Help or Hindrance? The Alcohol Industry and Alcohol Control in Portugal
Bibliographic record
Abstract
The influence of the alcohol industry, also known as "corporate political activity" (CPA), is documented as one of the main barriers in implementing effective alcohol control policies. In Portugal, despite an alcohol consumption above the European average, alcohol control does not feature in the current National Health Plan. The present research aimed to identify and describe the CPA of the alcohol industry in Portugal. Publicly-available data published between January 2018 and April 2019 was extracted from the main websites and social media accounts of alcohol industry trade associations, charities funded by the industry, government, and media. A "Policy Dystopia" framework, used to describe the CPA strategies of the tobacco industry, was adapted and used to perform a qualitative thematic analysis. Both instrumental and discursive strategies were found. The industry works in partnership with health authorities, belonging to the national task force responsible for planning alcohol control policies. Additionally, it emphasizes the role alcohol plays in Portuguese culture as a way to disregard evidence on control policies from other countries. This paper presents the first description of CPA by the alcohol industry in Portugal and provides evidence for the adoption of stricter control policies in the country.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".