Aspiring Ballerinas and Implications for Counselling Practice/Ballerines En Herbe et Implications Pour la Pratique Du Counseling
Notice bibliographique
Résumé
Miany young girls dream of becoming professional ballerinas. They spend years training rigorously, only to realize their goal is unattainable. Although this is an experience shared by many aspiring ballerinas, it has received little attention. The aim of this study is to increase understanding and mobilize support for future aspiring ballet dancers by shedding light on the experience of being unable to achieve the dream of dancing professionally. Implications for counselling practice are then addressed.BALLET TRAININGBallet training is a challenging experience associated with potentially both negative and positive consequences. Ballet dancers start training for their career in early childhood, many as early as 5 or 6 years of age (Pickman, 1987; Pulinkala, 2011; Wainwright & Turner, 2004). Some dancers are enrolled in their first ballet class as a result of their parents noticing them dancing around the house (Wulff, 1998). Others are enrolled on their own account, usually after being exposed to a ballet performance as a young child and then asking to be enrolled in a dance class (Pickard & Bailey, 2009; Wulff, 1998). As identified in Stinson, BlumenfieldJones, and van Dyke's (1990) hermeneutic phenomenological study of adolescent student dancers with backgrounds in jazz, tap, ballet, and modern, mothers are a common driving force behind young girls' discovery of dance. While many of the adolescents disliked dancing at first, they all reported that dance became an important part of their lives. Importantly, whatever the reason for developing an interest in ballet, the process of acculturation to the world of ballet begins at an early age, strengthening students' commitment to the art of dancing (Lee, 1988), and beginning their vocational training (Wulff, 1998).Training is foremost difficult-characterized by pressure, self-discipline, dedication, and perfectionism. Pressure has been identified as a key aspect of training, both pressure to meet dance standards in order to continue training (MacFarlane, 1994) and pressure to complete homework, meet new people, eat properly, manage finances, and live up to teachers' expectations (Cardinal, 2009). In order to manage the pressure and demands of training, ballet students need high levels of self-discipline (Hamilton, 1998).The intensiveness of ballet training (Pulinkala, 2011; Wainwright & Turner, 2004) also calls for high levels of concentration and dedication (Pickard & Bailey, 2009; Pickman, 1987). Hamilton, Solomon, and Solomon (2006) argued that dancers are especially known for dedication to their art. Dedication requires singularity of focus, and serious ballet students devote much of their youth to dancing. Much non-school time, strength, and energy are spent preparing for a ballet career (Alter, 1997; Pickman, 1987; Wainwright & Turner, 2004). Hopeful dancers attend daily ballet classes, which are highly competitive, as well as rehearsals and performances (Pulinkala, 2011; Wainwright & Turner, 2004). In addition to meeting the physical demands, ballet dancers must have a passion for dancing (Wainwright & Turner, 2004). To reach the level of a professional ballet dancer requires talent, hard work, and the drive to dance (Wainwright & Turner, 2004).Unsurprisingly, many dancers are described as perfectionists (Ackard, Henderson, & Wonderlich, 2004; Anshel, 2004; Schluger, 2010). Several negative consequences have been associated with perfectionism. For example, perfection- ism can (a) contribute to burnout (Hernandez, 2012); (b) lead to injury, health issues, and poorer quality of performance (Cardinal, 2009); (c) create feelings of inadequacy (Myburgh, Poggenpoel, & van Staden, 2009); and (d) contribute to negative body image (Myburgh et ah, 2009; Robson, 2001).Conversely, perfectionism has also been identified as a positive quality for dancers. Cumming and Duda (2012) found that dancers who have high personal standards but who are not overly concerned with making mistakes and doubting themselves had fewer concerns about their body. …
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 | 0,022 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,015 | 0,017 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,007 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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 ».