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十一年的性别数据可视化:迈向更具包容性的性别代表性的一步
IEEE transactions on visualization and computer graphics
|November 1, 2023
概括
这项研究分析了数据可视化中的性别代表性,发现色彩色调主导了性别数据显示,但不符合性别的性别在科学社区中代表性不足.
科学领域:
- 数据可视化 数据可视化
- 社会学 社会学 社会学
- 人与计算机的交互
背景情况:
- 性别是各种领域的常见人口统计数据维度,包括社会学和人机交互.
- 数据可视化设计师在视觉变量和文本中的选择可能无意中延续性别刻板印象和偏见.
- 数据表示的伦理含义在科学和面向公众的可视化中至关重要.
研究的目的:
- 分析性别在可视化中的数据维度是如何表示的.
- 建议对视觉变量进行考虑,并对与性别相关的数据进行注释.
- 提高人们对数据可视化中代表性别的细节的认识.
主要方法:
- 收集并编码了来自五个科学社区 (生物学,政治,社会学,可视化,HCI) 的性别可视化和标题.
- 包括图表公众和信息是美丽奖项的可视化.
- 分析了特定社区的表现类型,占主导地位的视觉道,以及不符合性别的不足.
主要成果:
- 性别数据的表示类型是科学界的特点.
- 颜色色调是编码性别信息的主要视觉道.
- 在分析的可视化中,不合规的性别认同显著不足.
结论:
- 视觉化设计选择对性别的描绘产生重大影响,可能会强化偏见.
- 社区特定的规范影响了可视化中的性别数据表示.
- 提供了改善性别数据可视化和大型数据收集机构的建议.
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