The Repercussions of Gender Bias in Data

Imagine trying to make a decision with only half the information. Today, nearly all organizations across the public and private sectors rely on data to make better decisions about everything from employee salaries to new legislation. Data provides decision makers insight into what the baseline is, where collective needs are, and where resources should be allocated. But half our world’s population—women—are underrepresented and many times completely unrepresented in these datasets.
Inaccurate data often results from gender bias in the design of surveys or questionnaires, or from someone other than the woman or girl responding to a survey on her behalf. Misrepresented or incomplete gender data collection yields results that misses the mark on understanding women’s needs or their economic and social contributions. Policies and initiatives around healthcare, education, economic opportunity and more are built based on what’s available—gender-biased data—and fail to fairly serve women and girls. How can we close the gender data gap and pursue the global ambition towards gender equality and a fuller understanding of the whole population?
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Uploaded: Feb 27, 2017

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Tags: Gender, woman, Data, girls, bias, feminism, world, healthcare, education, MultiVu 7889731

published 4 months ago