Data Feminism4,67 6 5 Forfatter: Lauren F. Klein, Catherine D'Ignazio Oplæser: Teri Schnaubelt
Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever "speak for themselves."
Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science.
Mere info om lydbogen:Forlag: Tantor Audio
Længde: 7T 37M