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Record W2083969888 · doi:10.1260/174795406779367819

Twirling through the Motions: Applying Motor Control Theory to Practice

2006· article· en· W2083969888 on OpenAlexaff
Leisha Strachan, Patricia L. Weir

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2006
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of WindsorQueen's University
FundersDeakin University
KeywordsCoachingPsychological interventionPsychologyControl (management)Motor controlPsychological controlMotor skillApplied psychologyCognitive psychologyDevelopmental psychologyComputer sciencePsychotherapistNeuroscienceArtificial intelligence

Abstract

fetched live from OpenAlex

This paper provides a link between theory and practice in the sport of baton twirling. An in-depth analysis of motor control theory applied to this sport will give some insight into how knowledge of motor control can impact the type of psychological interventions that may be most effective. A number of motor control issues are relevant to the sport of baton twirling. Although manual dexterity is the most prominent ability underlying baton twirling skills, other abilities such as multi-limb and eye-hand coordination, timing, and tracking also contribute to the intricacies of the sport. In reviewing the motor control research, many insights into the complexities of baton twirling are identified; these may prove beneficial to coaches regardless of what sport they are teaching. This review illustrates the importance of being mindful of the complexities involved in a sport and how effective psychological interventions may be developed through a thorough evaluation of a sport Implications for coaching are also 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 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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.010
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.015
GPT teacher head0.326
Teacher spread0.311 · 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 designTheoretical or conceptual
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

Citations4
Published2006
Admission routes1
Has abstractyes

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