MétaCan
Menu
Back to cohort
Record W145881555

Establishing a World Anti-Doping Code : WADA's impact on the development of an international strategy for anti-doping in sport

2006· article· en· W145881555 on OpenAlexaboutno aff
Caitlin A. Jenkins

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsDopingPolitical scienceMaterials scienceOptoelectronics
DOInot available

Abstract

fetched live from OpenAlex

The use and prevalence of performance enhancing drugs is not unique to modern sport. Reports of athletes striving to improve their physical abilities date back to third century BCE. Endeavoring to address the growing problem of doping in sport, WADA was created in 1999. This study evaluated how the formation of WADA impacted the development of an international strategy for anti-doping in sport. Conclusions were reached through the analysis of three primary sources of data: personal and organizational archives; media articles; and exploratory interviews. As revealed by the data, the formation of WADA brought together the necessary players to reach a solution for doping in sport. It provided a forum for sport and government to work co-operatively generating ideas and focusing thinking. It led to an awakening within government and sport to the complexities of doping; and it embodied an independent/credible organization while raising/maintaining global awareness and interest in doping. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .J46. Source: Masters Abstracts International, Volume: 45-01, page: 0306. Thesis (M.H.K.)--University of Windsor (Canada), 2006.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.044
GPT teacher head0.310
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueScholarship at UWindsor (University of Windsor)Same topicDoping in SportsFrench-language works237,207