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Record W2081453660 · doi:10.1080/1612197x.2006.9671781

Examining the relationship between perfectionism and trait anger in competitive sport

2006· article· en· W2081453660 on OpenAlexaffabout
John G.H. Dunn, John K. Gotwals, Janice Causgrove Dunn, Daniel G. Syrotuik

Bibliographic record

VenueInternational Journal of Sport and Exercise Psychology · 2006
Typearticle
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyAngerPerfectionism (psychology)TraitConstruct (python library)AthletesSocial psychologyFootballPersonalityDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the relationship between athletes’ perfectionist orientations and their dispositional tendencies to experience anger in sport. A sample of 138 male teenage high‐performance Canadian Football players (M age = 18.27 years, SD = .71) completed multidimensional domain‐specific measures of perfectionism and anger in sport. Canonical correlation (R C) results revealed a profile of maladaptive perfectionism (i.e., high personal standards combined with high concern over mistakes and high perceived coach pressure) that was significantly correlated with competitive trait anger (R C = .56) and the tendency to experience anger when playing poorly (R C = .47). That is, as athletes’ levels on three perfectionism dimensions increased (i.e., personal standards, concern over mistakes, and perceived coach pressure), so did their dispositional tendencies to experience anger in sport. The benefits of conceptualizing perfectionism as a domain‐specific construct, and the importance of considering all dimensions of perfectionism simultaneously when examining the functional nature of the construct in sport are discussed

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 score0.013
Threshold uncertainty score0.491

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 head0.043
GPT teacher head0.336
Teacher spread0.293 · 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

Citations75
Published2006
Admission routes2
Has abstractyes

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