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Record W2151337008 · doi:10.1123/tsp.16.2.160

Athletes’ Use of Imagery in the Off-Season

2002· article· en· W2151337008 on OpenAlexaff
Jennifer Cumming, Craig Hall

Bibliographic record

VenueThe Sport Psychologist · 2002
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsWestern University
Fundersnot available
KeywordsAthletesPsychologyCompetitive athletesBivariate analysisApplied psychologyPhysical therapyMedicineStatisticsMathematics

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the influence of competitive level on athletes’ use of imagery in the off-season and to examine whether their use of imagery was related to their physical and technical preparation. A total of 324 athletes completed a modified version of the Sport Imagery Questionnaire (SIQ; Hall, Mack, Paivio, & Hausenblas, 1998) that was designed to reflect an athletes’ use of imagery in the off-season. MANOVAs indicated that competitive level differences existed in athletes’ use of imagery in the offseason as well as in their use of physical and technical preparation for the upcoming season. More specifically, provincial and national level athletes engaged in significantly more imagery, regardless of the function, and physical and technical preparation than regional level athletes. In addition, bivariate correlations indicated that the more physical and technical preparation athletes engage in during the off-season, the more imagery they use.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.339
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), 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

Citations84
Published2002
Admission routes1
Has abstractyes

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