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Record W4322506630 · doi:10.3389/fspor.2023.1129390

Pathways to greater government accountability for breaches of their obligations in relation to doping in sport: A legal analysis

2023· article· en· W4322506630 on OpenAlexaff
David Pavot

Bibliographic record

VenueFrontiers in Sports and Active Living · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsAccountabilitySanctionsGovernment (linguistics)State (computer science)Political scienceSubject (documents)LawWork (physics)Relation (database)BusinessLaw and economicsSociologyEngineeringComputer science

Abstract

fetched live from OpenAlex

The State doping scandal in Russia has highlighted a major discrepancy in the fight against doping in sport: on the one hand, the signatories of the Word Anti-Doping Code (federations, NADO's, etc.) are subject to a very strict regime and incur serious sanctions, while on the other hand, States, when they massively violate the rules, do not risk very important consequences in international law. For example, high ranking officials as well as the Russian state apparatus have not been affected with a few exceptions such as the Moscow antidoping laboratory. The aim of this opinion paper is to present a reflection on the different avenues that could be envisaged to make governments more accountable, especially as work is underway on the topic. The development of a true government accountability regime would allow the system to be more balanced.

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)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.002
Science and technology studies0.0050.009
Scholarly communication0.0120.006
Open science0.0010.006
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Sports and Active LivingSame topicDoping in SportsFrench-language works237,207