The cultural rise of “big data” in the recent years has pressured a number of occupations to make an epistemological shift toward data-driven science. Though expressed as a professional move, this article argues that the push incorporates gendered assumptions that disadvantage women. Using the human resource occupation as an example, I demonstrate how normative perceptions of feminine “soft skills” are seen as irreconcilable with the masculine “hard numbers” of a data-driven epistemology. The history of human resources reflects how assumptions of a biological fit with an occupation limit what women can convincingly describe as her skillsets. However, challenging this cannot stay within the confines of the occupation itself. To undo sexist thinking, it is necessary to understand the broader networks of patriarchal power that dictate how value is defined in corporate environments, especially within other high status professions in business.
CITATION STYLE
Hong, R. (2016). Soft skills and hard numbers: Gender discourse in human resources. Big Data and Society, 3(2). https://doi.org/10.1177/2053951716674237
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