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Record W3123783217 · doi:10.47863/nhsf7128

A Comparison of the Emotional Intelligence and Psychological Skills of National and International Taekwondo Referees

2020· article· en· W3123783217 on OpenAlexafffund
Maghsoud Nabilpour, Mohammad Hossein Samanipour, Timothy Baghurst, Saeed Bagha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsCape Breton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEmotional intelligencePsychologyAthletesNationalityApplied psychologyDemographicsLeagueSport psychologySocial psychology

Abstract

fetched live from OpenAlex

Officiating is a challenging role within sports that requires many psychological skills as well as emotional intelligence, the ability to recognize and moderate personal emotions and the emotions of others, while simultaneously processing the information to make an informed decision about the present situation. Although many studies have investigated these characteristics within athletes and coaches to improve sports performance, officials overseeing these competitive environments have been largely ignored. Therefore, the purpose of this study was to investigate the psychological skills and emotional intelligence of national and international taekwondo referees. Participants were 10 international and 10 national referees who completed four measures of psychological skills and emotional intelligence. National referees scored significantly higher on emotional intelligence and most psychological skills. This was surprising, suggesting either national referees feel more emotionally and psychologically competent perhaps from more regular practice and/or international referees are more self-aware of their limitations and less likely to score themselves highly on a self-report measure. Future research should consider comparison of referees across genders, nationality, levels, sport, and other demographics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.997

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)0.0040.000

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 head0.235
GPT teacher head0.457
Teacher spread0.222 · 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.

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

Citations5
Published2020
Admission routes2
Has abstractyes

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