芭蕾合作网络中的结构性性别失衡

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Yessica Herrera-Guzmán, Eun Lee, Heetae Kim
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引用次数: 2

摘要

芭蕾舞是一种以女性为主的主流表演艺术,在领导职位上表现出明显的性别失衡。但是,协作的结构构成对-à-vis外地的性别代表性仍未加以探讨。本研究探讨芭蕾创作中的性别劳动力构成及合作模式。我们的研究结果揭示了芭蕾舞创作中的性别差异与性别合作模式相一致,女性比男性占据更多的外围网络位置。生产力差异表明,与男性相比,女性获得了20-25%的芭蕾舞作品。数学推导出的认知错误表明,在芭蕾合作网络中,低估了女性艺术家的代表性,这可能会影响女性在该领域的职业生涯。我们的研究强调了女性在芭蕾创作中面临的结构性失衡,并强调了在芭蕾产业中需要一个更加包容和平等的专业环境。这些见解有助于更广泛地理解艺术领域的结构性性别失衡,并可以为文化组织提供关于在芭蕾舞中更好地代表女性领导者的潜在平权行动的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Structural gender imbalances in ballet collaboration networks

Structural gender imbalances in ballet collaboration networks

Ballet, a mainstream performing art predominantly associated with women, exhibits significant gender imbalances in leading positions. However, the collaboration’s structural composition vis-à-vis gender representation in the field remains unexplored. Our study investigates the gendered labor force composition and collaboration patterns in ballet creations. Our findings reveal gender disparities in ballet creations aligned with gendered collaboration patterns and women’s occupation of more peripheral network positions than men. Productivity disparities show women accessing 20–25% of ballet creations compared to men. Mathematically derived perception errors show the underestimation of women artists’ representation within ballet collaboration networks, potentially impacting women’s careers in the field. Our study highlights the structural imbalances that women face in ballet creations and emphasizes the need for a more inclusive and equal professional environment in the ballet industry. These insights contribute to a broader understanding of structural gender imbalances in artistic domains and can inform cultural organizations about potential affirmative actions toward a better representation of women leaders in ballet.

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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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