US EditionOnus on Athletes to Let Drug Testers Know Where They Are Under “Whereabouts” Rules
SIMCOE COUNTY, ONTARIO, JUL 22 – Penny Oleksiak missed three whereabouts filings from October 2024 to June 2025, leading to a provisional suspension under World Aquatics anti-doping rules, officials said.
- Penny Oleksiak, a 25-year-old Toronto swimmer, withdrew from the world championship starting July 26, 2025, in Singapore after a whereabouts violation.
- Oleksiak did not maintain current whereabouts details, resulting in a whereabouts failure—defined by three missed tests or filing oversights within a 12-month span—from October 2024 to June 2025.
- Canadian athletes receive training on submitting whereabouts data through an online e-learning module, with email reminders issued one month and 15 days before quarterly deadlines, yet time zone changes and fluid schedules can cause mistakes.
- Oleksiak described her violation as an administrative mistake unrelated to banned substances and affirmed she has always been a clean athlete in a since-deleted social media post.
- Oleksiak withdrew from competition and agreed to a temporary suspension in accordance with the anti-doping regulations set by World Aquatics, underscoring the continuing challenges athletes face in maintaining accurate whereabouts information.
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Onus on athletes to let drug testers know where they are under “whereabouts” rules
A chunk of an Olympic and Paralympic athlete’s life is spent telling drug testers where they will be every day and every night. Failure to provide that information can damage an athlete’s eligibility to compete, even if they’ve never taken a banned substance.
·Toronto, Canada
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Bradford Today+12 Reposted by 12 other sources
Onus on athletes to let drug testers know where they are under "whereabouts" rules
A chunk of an Olympic and Paralympic athlete's life is spent telling drug testers where they will be every day and every night.
·Bradford West Gwillimbury, Canada
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Total News Sources17
Leaning Left8Leaning Right1Center1Last UpdatedBias Distribution80% Left
Bias Distribution
- 80% of the sources lean Left
80% Left
L 80%
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