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Record W2165068323 · doi:10.1123/tsp.14.2.119

The Four Ws of Imagery Use: Where, When, Why, and What

2000· article· en· W2165068323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Sport Psychologist · 2000
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsWestern University
Fundersnot available
KeywordsAthletesPerspective (graphical)Elite athletesMental imageCompetition (biology)PsychologyApplied psychologyPsychological interventionComputer scienceCognitionMedicinePhysical therapyArtificial intelligenceEcology

Abstract

fetched live from OpenAlex

The purpose of the study was to identify and describe the four Ws of athletes’ imagery use: where, when, why, and what. Due to the in-depth nature of the questions being asked, a qualitative approach was employed. The participants were 14 elite athletes (7 male and 7 female), representing 7 different sports. A constant comparative method of analysis was conducted by two investigators. A conceptual framework was developed to display the four Ws of imagery use during and outside practice, as well as for pre-competition, competition, and post competition. Results from the present study indicated where and when athletes use imagery, and extended previous findings on why and for what athletes use imagery. It was proposed that a better understanding of the athletes’ images can serve as a guide to future research and from a practical perspective, facilitate the development of more effective imagery interventions.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.992

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 studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.040
GPT teacher head0.320
Teacher spread0.280 · 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