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Record W2791579054 · doi:10.1136/bjsports-2017-098299

Geolocalisation of athletes for out-of-competition drug testing: ethical considerations. Position statement by the WADA Ethics Panel

2018· article· en· W2791579054 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBritish Journal of Sports Medicine · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsMcGill UniversityUniversity of Alberta
Fundersnot available
KeywordsAthletesPosition statementCompetition (biology)Position (finance)BusinessInternet privacyEthical issuesPublic relationsPsychologyMedicineComputer securityPolitical scienceApplied psychologyEngineering ethicsComputer scienceEngineeringFamily medicinePhysical therapyFinance

Abstract

fetched live from OpenAlex

Through the widespread availability of location-identifying devices, geolocalisation could potentially be used to place athletes during out-of-competition testing. In light of this debate, the WADA Ethics Panel formulated the following questions: (1) should WADA and/or other sponsors consider funding such geolocalisation research projects?, (2) if successful, could they be proposed to athletes as a complementary device to Anti-Doping Administration and Management System to help geolocalisation and reduce the risk of missed tests? and (3) should such devices be offered on a voluntary basis, or is it conceivable that they would be made mandatory for all athletes in registered testing pools? In this position paper, the WADA Ethics Panel concludes that the use of geolocalisation could be useful in a research setting with the goal of understanding associations between genotype, phenotype and environment; however, it recognises that the use of geolocalisation as part of or as replacement of whereabouts rules is replete with ethical concerns. While benefits remain largely hypothetical and minimal, the potential invasion of privacy and the data security threats are real. Considering the impact on privacy, data security issues, the societal ramifications of offering such services and various pragmatic considerations, the WADA Ethics Panel concludes that at this time, the use of geolocalisation should neither be mandated as a tool for disclosing whereabouts nor implemented on a voluntary basis.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.087
GPT teacher head0.360
Teacher spread0.273 · 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