The evidence-base and development of a tobacco-free stadium declaration for Europe
Bibliographic record
Abstract
The paper will present new data on the frequency of tobacco-free policies at football stadiums across UEFA's 55 member associations, including data on mandatory and voluntary policies, and levels of adherence by fans. With reference to this new evidence-base, the author will then detail new partnerships with UEFA, national football associations, Healthy Stadia and tobacco-control agencies in the development of a declaration. The declaration will commit national associations and/or league operators to embed tobacco-free stadia policies and enforcement within stadium regulations and conditions of sale for tickets to matches, and will be supported by a wide range of assets including guidance, case studies and training modules. It is anticipated that national associations will adopt a phased approach to implementing the primary aims of the declaration, with a commitment to completing the process within 24 months of signing the declaration. The declaration will be launched in June 2019 at the UEFA Nations League Finals in Portugal.
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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 | 0.201 | 0.346 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".