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Record W4386604057 · doi:10.1093/eurpub/ckad133.274

O.6.2-4 Please stop claiming that elite sport influences the general population to practice physical activity!

2023· article· en· W4386604057 on OpenAlexaboutno aff
Alexis Lion, Anne Vuillemin, Florian Léon, Charles Delagardelle, Aurélie Van Hoye

Bibliographic record

VenueEuropean Journal of Public Health · 2023
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsElitePsycINFOPopulationAthletesElite athletesPsychologySports medicinePolitical scienceMedicineMEDLINEPhysical therapyLawPoliticsEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Purpose The Paris 2024 Olympic Games Organisation Committee claims that “another impact of the Games on society is reflected in the increase in the practice of sports”. Decision-makers and policymakers still use the trickle-down effect to legitimize spending public money to support elite sport events and/or to finance elite sport programs/athletes. We therefore wanted to investigate if this effect was not a myth. Methods We conducted structured Boolean searches across five electronic databases (Pubmed, JSTOR, Web of Sciences, Sportdiscus, and PsycInfo) from January 2000 to August 2021 using the following equation: ((“elite” OR “high level” OR “performance”) OR (“Olympic*” AND *Games”) AND (“sport” OR “athletes” OR “players”)) AND ((“physical activit*” OR “sport” OR “exercise”) AND (“participation” OR “practice”)). We also conducted manual searches using the reference lists of the recovered records. Peer-reviewed studies in English were included if the effects of hosting elite sport events, elite sport success, and elite sport role-modelling on physical activity (PA) or sport practice in the general population were measured. Results We identified 12,563 articles and included 36 articles. Most studies used data from the United Kingdom (n = 10), Australia (n = 5), Canada (n = 4), and multiple countries (studies using data from several countries) (n = 4). Seven articles investigated more than one effect of elite sport. Most studies investigated the effect of hosting elite sport events (n = 27), followed by elite sport success (n = 16) and elite sport role-modelling (n = 3). Most studies did not observe an effect of hosting elite sport events, elite sport success, or elite sport role-modelling on PA/sport practice in the general population. We also did not observe any evidence of elite sport effects according to the age range, the geographical scale, or time. Conclusions There is no evidence supporting an effect of elite sport in increasing PA or sport participation in the general population. Decision-makers and policymakers should not use the tickle-down effect of elite sport to legitimize spending public money to support elite sport events and/or to finance elite sport programs/athletes. They should invest in other strategies such as those recommended by the World Health Organization.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.477
Threshold uncertainty score0.746

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0020.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.4770.143

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.

Opus teacher head0.173
GPT teacher head0.424
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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