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Criminal Legal Assessment of Harm Caused during Sports Activities in Common Law Countries

2025· article· en· W4410055195 on OpenAlexaboutno aff
M. K. Ayrapetyan

Bibliographic record

VenueActual Problems of Russian Law · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsHarmLawCriminal lawPolitical scienceCriminologyPsychology

Abstract

fetched live from OpenAlex

The subject of the study is foreign law enforcement practice on bringing athletes to criminal liability for causing harm during sports competitions. In order to determine the acceptable level of violence in sports games and the limits of an athlete’s consent to causing harm, the author examines the approaches of the courts of precedent law countries, namely the UK, Canada and the USA. The concepts of rules of the game and part of the game are analyzed, and their advantages and disadvantages are identified. The experience of foreign countries in holding athletes accountable in contact sports involving physical contact–hockey, football, basketball–is summarized. The problems of finding universal criteria for assessing a player’s actions are revealed, and Canadian judicial practice on this issue is examined in detail. The reasonably foreseeable hazards approach proposed by American legislators and courts is examined. The author comes to the conclusion about the non-systemic and selective nature of criminal prosecutions for sports violence and the dominance of the position of non-interference of criminal law in the field of sports, which corresponds to the principle of autonomous legal regulation of this sphere.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.984

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.322
Teacher spread0.305 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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