A Feminist Analysis of the Impact of COVID-19 on Olympic Female Athletes from Canada and the People’s Republic of China
Notice bibliographique
Résumé
Gender equality in sports acquired unprecedented discussion in the past few decades with the efforts of sports organizations such as the United Nations (UN), athletes, professionals, and scholars worldwide. Girls’ participation, women’s media representation, participation of transgender athletes, equal opportunity, equal pay, etc. drew attention and awareness successfully. However, the outbreak of COVID-19 has been limiting the achievement of women in sports due to the cancellation of sports events, postponement of the Olympic Games, stay-at-home orders in lockdown, and restrictions on health measurements. This study utilized methods of semi-structured interviews, media analysis, and comparative analysis to examine the barriers faced by female Olympic athletes, along with their coping strategies during the COVID-19 pandemic. A comparison between Chinese and Canadian female athletes was implemented to gain insight into the barriers they struggled with in the pandemic, including the level of adaptation to COVID-19, length of building resilience to return to sports (RTS), accessibility of training facility, mental health problems, and other possible barriers. The results in this thesis indicated that Canadian female athletes had more significant obstacles in training whereas Chinese female counterparts did not perceive they had a considerable challenge since the pandemic. Despite the differences, the main similarity between Canadian and Chinese female athletes was the delay of the Olympic Games allowed them to re-concentrate on training and disassociate from the stressful ambience. The differences between the athletes’ experiences in the pandemic were due to different levels of accessibility to resources: female athletes in China acquired secured environments for training while Canadian female athletes had more opportunities to find various official resources online. Chinese athletes had better training accessibility and supervision from coaches while Canadian athletes had relatively limited access to training facilities. Overall, the pandemic increased gender inequality for elite female athletes to participate in sports and support systems. Sports organizations should comprehensively review and improve their operations to learn from the pandemic in order to support elite female athletes.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,022 | 0,006 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».