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Record W4405043145 · doi:10.1016/j.peh.2024.100317

Decoding unintentional doping: A complex systems analysis of supplement use in sport

2024· article· en· W4405043145 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePerformance Enhancement & Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
FundersWorld Anti-Doping Agency
KeywordsDecoding methodsComputer sciencePsychologyTelecommunications

Abstract

fetched live from OpenAlex

• This study has demonstrated the complex interactions between tasks, and the stakeholders associated with supplement use in sport in an Australian context. • This study has demonstrated that regulatory oversight, manufacturing, sale, and distribution processes are critical areas where substandard performance can potentially create conditions for unintentional doping downstream for athletes. • The findings indicate that for the prevention of unintentional doping through supplement use, policy interventions will need to shift away from the typical focus on athletes and their support personnel, to encompass a broader systemic focus. Unintentional doping though supplement use is an ongoing issue that has severe professional and personal impacts on athletes. Though the issue is well known, there are key knowledge gaps regarding the role of different stakeholders both in creating and managing unintentional doping. The current study aimed to identify the influential tasks and stakeholders within the Australian sport system that are associated with supplements. A Hierarchical Task Analysis (HTA) was developed during a subject matter expert workshop (n = 12) to decompose the supplement use in sport ‘system’ into a hierarchical structure of goals, sub-goals, operations, and plans. A task network was developed during the SME workshop and based on the first level sub-goals of the HTA. Network analysis was then applied to determine the interdependency and influence of system tasks and stakeholders. Network metrics included Density, Out-degree centrality, In-degree centrality, Betweenness centrality, Closeness centrality, and Eigenvector centrality. In total, 15 first level sub-goals were identified which were further decomposed into 71 sub-goals and operations. The overall identified goal of athletes taking supplements was to optimise health, performance, recovery, image, and achieve optimal weight. Within this overall goal, numerous tasks are required to be performed including research, manufacturing and regulation of supplements, maintaining clean sport, to the administration of supplements by athletes, to subsequent assessments of their efficacy. The most influential tasks within the system include ‘maintaining clean sport’ by anti-doping authorities, and ‘marketing/advertising’ of supplements by supplement companies. Influential stakeholders within the system included ‘anti-doping agencies’, ‘athlete support personnel’, and ‘sponsors’. The analysis has demonstrated that multiple and varied stakeholders have specific roles to play in preventing unintentional doping. The findings suggest that for the prevention of unintentional doping through supplement use, interventions will need to shift away from the typical focus on athletes and athlete support personnel, to encompass a broader systemic focus.

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)0.002
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 score0.316
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.090
GPT teacher head0.391
Teacher spread0.301 · 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