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Record W2966165241 · doi:10.1080/02640414.2019.1643648

The role of the athletes’ entourage on attitudes to doping

2019· article· en· W2966165241 on OpenAlexfundno aff
Vassilis Barkoukis, Lauren Brooke, Nikos Ntoumanis, Brett Smith, Daniel F. Gucciardi

Bibliographic record

VenueJournal of Sports Sciences · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsAthletesPsychologyPhysical therapySocial psychologyMedicine

Abstract

fetched live from OpenAlex

The present study investigated athletes' and coaches' beliefs about the role of athletes' entourage in deterring or promoting doping. Competitive athletes and coaches in Greece and Australia took part in semi-structured interviews. Our analysis of the interviews produced five main themes: coach influence, peer influence, doping stance, doping stigma, and entourage's culture. Overall, coaches and peers having a close and trusty relationship with the athletes were considered most influential with respect to doping-related decisions. The majority of the athletes held a strong anti-doping stance but could not articulate why they held this position. This inability could be ascribed to the stigmatization of doping which led to lack of knowledge and anti-doping education. Finally, an anti-doping culture in the athletes' environment was considered central to an anti-doping stance. The study findings provide valuable information towards a comprehensive understanding of the role athletes' entourage can play in shaping athletes' attitudes and decision for doping.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.307
Teacher spread0.291 · 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 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

Citations47
Published2019
Admission routes1
Has abstractyes

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