’We are not all in the same boat. We are in the same storm. Some are on super-yachts. Some have just the one oar.’ How COVID-19 exaggerated global inequities in professional sport
Bibliographic record
Abstract
The important mental, physical, social and fiscal role of organised, professional sport in our lives as athletes, athlete support personnel, consumers and various stakeholders was highlighted by the gaping hole its absence left after global COVID-19 lockdowns and restrictions brought professional sporting activities to a standstill.However, as seen in various industry sectors, clinical, and social settings, the burdens of the COVID-19 pandemic were borne unequally.While the clinical effects of the virus were similar worldwide, their implications were superseded by the different socioeconomic contexts in which they occurred.This editorial highlights how COVID-19 exacerbated global inequities in professional athletes' physical, mental and fiscal health outcomes and how those in low and middle-income countries (LMICs) were left further behind.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".