Propositions and Recommendations for Enhancing the Legacies of Major Sporting Events for Disadvantaged Communities and Individuals
Bibliographic record
Abstract
This consensus statement is the outcome of comprehensive collaboration through an international working group on the disparities in the legacies of major sporting events, specifically for communities and individuals from disadvantaged backgrounds (CIDBs). The workshop brought together scholars to discuss current challenges and develop four propositions and recommendations for event leveraging, policy stakeholders, and researchers. The propositions included (1) the nature of “disadvantage” needs to be recognized and the specific targeted CIDBs in each event context must be carefully identified or clearly defined; (2) CIDBs should be considered as an integral part of the whole event hosting cycle to ensure legacy inclusivity; (3) dedicated event leverage, sufficient financial backing, and resource commitments for CIDBs are needed; and (4) it is critical to establish a system of legacy governance for CIDBs. The recommendations aim to inform change in practice and ensure lasting positive legacies for the communities that need them most.
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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 | 0.058 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.007 | 0.011 |
| Research integrity | 0.018 | 0.014 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".