13. Data visualization literacy: A feminist starting point

C. D’Ignazio, Rahul Bhargava
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引用次数: 4

Abstract

We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineeering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces where, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives’.
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13. 数据可视化素养:女权主义的起点
我们断言,视觉数字素养,实际上是所有的数据素养,必须以当前通过数据产生和复制的人际关系和影响是不平等为出发点。同样,白人男性在数据相关领域的比例仍然过高,尽管其他STEM(科学、技术、工程和医学)领域已经设法缩小了性别差距。为了解决这些不平等,我们引入了基于女权主义理论、过程和设计的教学方法。通过三个案例研究,我们研究了女权主义可能必须提供的可视化素养,其目标是培养女性和代表性不足的群体的自我效能感,以处理数据,并创造学习空间,如Philip等人(2016)所述,“群体影响,抵制和改变影响他们生活的日常和正式权力过程”。
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