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Record W1964609237 · doi:10.1037/1076-898x.10.4.219

Predicting Performance Times From Deliberate Practice Hours for Triathletes and Swimmers: What, When, and Where Is Practice Important?

2004· article· en· W1964609237 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

VenueJournal of Experimental Psychology Applied · 2004
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of WindsorMcMaster UniversitySimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsSprintAthletesPsychologyClinical PracticePhysical therapyApplied psychologyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

In Studies 1 and 2, the authors evaluated deliberate practice theory through analyses of the relationship between practice and performance for 2 populations of athletes: triathletes and swimmers, respectively. In Study 3, the authors obtained evaluations of practice from athletes' diaries. Across athletes, length of time involved in fitness activities was not related to performance. For the triathletes, a significant percentage of variance in performance was captured by practice. This was not so for sprint events for the swimmers, in which gender was a significant predictor. In the diaries, physical activities were perceived as enjoyable. In contrast to the results obtained from questionnaires, enjoyment did not covary with an activity's relevance to improving performance. Although these findings highlight the importance of sport-specific practice, the authors question a domain-independent account of expertise based on deliberate practice.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score1.000

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.363
Teacher spread0.338 · 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