Predicting moral behaviour in sport: individual and interactive relationships involving motivational climate, gender, and perfectionism
Notice bibliographique
Résumé
A large proportion of Canadian youth aged 15 to 19 ? approximately 60 percent ? participate in organized sport (Canadian Fitness & Lifestyle Research Institute, 2015). Given this significant number, popular media portrayals of the behaviour of athletes have the potential to shape the behaviour of youth athletes (Bush, Martin, & Bush, 2004). Appropriate behaviour is determined in part by the internalized morals and values one has adopted (Bandura, 1991). With the exception of family, sports provide one of the most influential social environments with which an individual may be involved (Bruner, Boardley, & C?t?, 2014). Throughout the course of a competition, incidents may occur that result in athletes choosing to behave in a manner that results in positive outcomes for others, or choosing to behave in a way that results in negative outcomes for others. For example, Sarah Tucholsky was a senior outfielder for the University of Western Oregon?s softball team when she hit her first career home run (CBS News, 2008). In her excitement, she missed first base, and when she turned back to tag the base, she injured her knee. Unable to run, the opposing team?s first base woman and their shortstop asked permission and carried Tucholsky around the bases resulting in a three-run victory for Tucholsky?s team. In contrast, Elizabeth Lambert was a defender with the University of New Mexico?s women?s soccer team when she became infamous following a game in which she exhibited several aggressive and decidedly unsportspersonlike behaviours. Throughout the game she punched, tripped, tackled, and finally pulled an opposing player to the ground by her ponytail (Clayton, 2010), behaviours that eventually earned her a yellow card (a penalty in soccer). \nIncidents of positive and negative behaviour in sport, as exemplified by the experiences of Sarah Tucholsky and Elizabeth Lambert described earlier, have received considerable attention from both the public and the media highlighting the value of investigating moral behaviour in sport (Perry, Clough, Crust, Nabb, & Nicholls, 2015). How athletes choose between positive and negative behaviour may be influenced by many factors, including the influence of their personality and the influence of the environment. An even greater understanding of moral behaviour in sport may be obtained by simultaneously considering the interaction between personality and environmental factors (Bandura, 1991; Hodge & Lonsdale, 2011; Kavussanu, 2012). The present study was conducted in line with this contention.
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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».