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Record W2955788959

The youth sport environment: A descriptive analysis

2010· article· en· W2955788959 on OpenAlexaff
Elaine Raakman, Kim D. Dorsch, Daniel Rhind

Bibliographic record

VenueJournal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository) · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsFootballCoachingPsychologyAthletesContext (archaeology)Descriptive statisticsClubYouth sportsAdvertisingApplied psychologySocial psychologyPolitical sciencePhysical therapyMedicineGeographyBusinessLaw
DOInot available

Abstract

fetched live from OpenAlex

To what extent does the phenomenon of poor behaviour occur in youth sport? Some experts posit that roughly 10% of athletes are exposed to unacceptable coaching behaviours within the youth sport context (David, 2005). However, few studies have attempted to quantify the extent to which poor behaviours occur by all youth sport participants (coaches, players, and spectators). The purpose of this study is to use data provided by an independent sport monitoring program, Justplay Behavioural Management Program (JBMP), to describe these behaviours. Through the JBMP officials are asked to rate the behavioural conduct of coaches, players, and spectators on a scale from 1 Very Good to 5 Very Poor. Ratings of 4 and 5 are known as critical incidents (CI; conduct deemed unacceptable by the official). This descriptive analysis examines multiple youth sports (hockey, baseball, football) over three seasons with regard to the extent of CI by all the participant groups. Analyses show that CI occurred in 40% of all hockey games, 37% of football games, and 36% of baseball games. Of these CI, coaches account for 42.6% (42.5% hockey; 34.7% baseball, 50.7% football), players for 26.7% (29.5% hockey; 31.1% baseball, 19.5% football), and spectators for 30.2% (26.7% hockey; 34.2% baseball, 29.6% football). These numbers indicate behaviours, which may have long-term negative effects on participants, occur to a worrisome degreeAcknowledgments: 1. David, P., Human Rights in Youth Sports: A Critical Review of Children's Rights in Competitive Sports, Routledge, New York, 2005.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.200
Teacher spread0.184 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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