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Record W2802293163 · doi:10.1080/19406940.2018.1437058

Protecting or undermining the integrity of sport? The science and politics of the McLaren report

2018· article· en· W2802293163 on OpenAlexaboutno aff
Vassil Girginov, Jim Parry

Bibliographic record

VenueInternational Journal of Sport Policy and Politics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
FundersGrantová Agentura České Republiky
KeywordsPoliticsPolitical sciencePublic administrationScientific integritySociologyLawEngineering ethicsEngineering

Abstract

fetched live from OpenAlex

This study interrogates the ramifications for the integrity of sport of the McLaren Report (2016a McLaren, R., 2016a. The independent person report. Montreal: WADA, Available from: https://www.wada-ama.org/sites/default/files/resources/files/20160718_ip_report_newfinal.pdf [Accessed 3 January 2017]. [Google Scholar]) into doping allegations concerning the Sochi Olympics. Using an evidence-based approach to policymaking, the main claims of the report are subjected to scrutiny. The analysis suggests that McLaren’s report seriously undermines the integrity of Olympic sport for four main reasons:(i) Contrary to the historic neutrality of World Anti-Doping Agency (WADA), it took a political stance by implicating a nation state in wrong-doing without presenting sufficient evidence;(ii) WADA undermined trust in the decision-making process concerning the enforcement of compliance with its Code by using a highly questionable methodology for gathering information;(iii) WADA exposed its own inadequacies by allowing top athletes to use banned substances, and(iv) WADA undermined its main mandate as an enforcer of compliance by turning this global organisation into an ‘on-demand police service’.We conclude thus: even if you think you are doing the right thing, you must not do the right thing with the wrong process because right is also enshrined in the process. The ends cannot justify the means.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
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 head0.079
GPT teacher head0.409
Teacher spread0.331 · 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.

Study designTheoretical or conceptual
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

Citations7
Published2018
Admission routes1
Has abstractyes

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