What is the influence of music on performance in practice and competition among university competitive fencers?
Notice bibliographique
Résumé
Fencing as a sport and music as an expressive form are two topics that may seem very distant in comparison, but both have many aspects that are intertwined. The purpose of this study was to understand how music is used within practice and competition settings and how rhythm, tempo and timing in fencing might be influenced by music. This study used grounded theory and its three-phase thematic analysis and applied a social-constructivist lens. The research question was: What is the influence of music on performance in practice and competition among university competitive fencers? The participants were interviewed using semi-structured interviews and the researcher kept retrospective notes on observations as an insider to the fencing community. The main findings were split into two groups that included practice and competition. Practice music influence showed that music was used to increase motivation but could also cause distraction from the practice. It also showed how one learned to develop fencing rhythm using music, and how auditory cues from music and from saying sounds that correspond to physical movements help with development of timing. Other findings were that fencers have practice structured around the way they learn, moving from learning in parts to wholes or easy to complex. Also noted was that each weapon has its own style that is free to be discovered and developed. Competition music influence was discovered to be almost non-existent other than for the use of pre-competition preparation and was used sometimes between bouts for relaxation purposes. Other findings were that due to external stressors, fencers tend to not be aware of what their body is doing. In their minds, the action feels correct, but it might have been too big or small or too fast or slow. Also, partner rhythm within a competition is difficult to manipulate as both opponents are trying not to follow each other’s footwork. Music seems to have an influence on those who use it to their advantage, but is connected to the athletes, coaches, and their way of learning.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».