What health-related messages are promoted during mega sports events? A multi-country study of Paris 2024 Olympic and Paralympic Games
Bibliographic record
Abstract
Purpose This study is a first exploration of health promotion messages during a mega sports event. In total, 12 countries were examined for how health-related messages were communicated in relation to the Paris 2024 Olympic and Paralympic Games via global and national partners. Design/methodology/approach In this study, 12 countries were examined to investigate how the Paris 2024 Olympic and Paralympic Games promoted health. The Global Health Promotion and Sport Events Survey was applied to identified messages produced by global sponsors and national-level sponsors that related to community health, physical health, mental health, environmental health and nutritional health. Findings In total, 238 health-related messages were examined. The vast majority of these messages came from commercial, for-profit entities. When only one type of health was presented, this was often either community/social health, physical health or mental health. Environmental health and nutritional health appeared least often. Nearly half of the messages involved a combination of health types. Research limitations/implications Paris 2024 was used by many corporate partners and National Olympic Committees to actively promote health-related messages around the world. A strength of this study was that it involved data collection from a range of countries. Practical implications There are increasing concerns about detrimental effects from commercial determinants of health. Governing bodies of sport are encouraged to review partnerships which do not promote health. Social implications There is opportunity to use the mega events to promote more specific actions relating to health, since the Olympic and Paralympic Games are occasions where social connection and celebration are likely to be inevitable. Originality/value This study offers an audit tool and sets a benchmark for understanding how health promotion messages are manifested at sport events.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".