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Record W2179912770

Study of the issue of excessive violence in competitive sports in the United States and Canada

2011· article· en· W2179912770 on OpenAlexaboutno aff
Wang Shui-ming, YE Jian-feng

Bibliographic record

Venuejournal of physical education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationObstacleChinaCompetition (biology)LeagueJurisdictionAutonomyLawPolitical scienceCriminal lawCriminal jurisdictionBusiness
DOInot available

Abstract

fetched live from OpenAlex

In recent years,with the booming of world competitive sports,the behaviors of excessive violence in competitive sports occurred from time to time,and their social hazardness is becoming perceivable.As a big nation of competitive sports,the United States and Canada have unique understanding about and experiences in determin-ing the nature of and penalties for excessive violence,their ways to deal with such behaviors include legislation,case law and league.Criminal prosecution of the behaviors of excessive violence in sports is feasible,but will en-counter substantial obstacles,which include conceptional obstacles and constitutional obstacles,in which the big-gest obstacle is the principle of consent.Consent as a ground for defense can effectively exclude criminal liabili-ties.In China,there is no unified standard for dealing with such behaviors.By referring to the experiences of the United States and Canada,the author proposed that China should make improvements gradually in 4 aspects,i.e.perfecting sport specific legislation,intensifying jurisdiction,promoting the autonomy of sports leagues,and strengthening the scientific study of competition rules.

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)0.000
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 score0.203
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.318
Teacher spread0.302 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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