MétaCan
Menu
Back to cohort
Record W4200002377 · doi:10.3390/jrfm14120603

Doping Sanctions in Sport: Knowledge and Perception of (Legal) Consequences of Doping—An Explorative Study in Austria

2021· article· en· W4200002377 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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsSanctionsAthletesPerceptionControl (management)Public relationsPsychologyPolitical scienceBusinessSocial psychologyLawMedicineManagement

Abstract

fetched live from OpenAlex

Anti-doping rule violations (ADRVs) can lead to sports-related and legal sanctions, thus, being knowledgeable is important. Research into this knowledge and how athletes and their support personnel (ASP) perceive the control mechanisms and the appropriateness of (legal) sanctions is still scarce. This explorative study aimed to examine the knowledge and perception of existing (legal) sanctions in Austria, by distributing a questionnaire to Austrian athletes and ASP covering the topics of knowledge related to legal and sports-related consequences associated with a specific ADRV presented in a case study, their trust and satisfaction with specific agencies (based on the European Social Survey (ESS)) and perceived efficiency and effectiveness of the doping control system. Data were analyzed descriptively. All respondents (N = 59) agreed on a ban from sport to be appropriate. Knowledge about legal consequences and the trust in the judiciary and the sport governing bodies was moderate (6.82 out of 10). Perceived appropriate consequences were on average higher than the likely sanctions to be faced. Future prevention should include trust building measures in the institutions and the control system, improvement in terms of access to law and education for the target group and critical reflection on the existence of social norms. Furthermore, the implementation of risk management aspects should be part of future approaches.

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)0.001
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 score0.048
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.324
Teacher spread0.294 · 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