Gender bias in data impacts policy decisions from "summary" of Invisible Women by Caroline Criado Perez
Gender bias in data is a pervasive issue that has far-reaching consequences, especially when it comes to policy decisions. When data is collected without taking gender into account, it can lead to skewed results that do not accurately represent the realities of women's lives. This lack of representation can have serious implications for the formulation and implementation of policies that affect women. For example, when data on employment is collected without distinguishing between men and women, it can mask the disparities that exist in the workforce. This means that policies aimed at promoting gender equality in the workplace may not be as effective as they could be because they are based on incomplete or inaccurate information. Without a clear understanding of the challenges women face in the workforce, policymakers may not be a...
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