Invisible Women

Invisible Women : Data Bias in a World Designed for Men

4.36 (90,697 ratings by Goodreads)
4.36 (90,697 ratings by Goodreads)

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Description

Winner of the 2019 Financial Times and McKinsey Business Book of the Year Award
Winner of the 2019 Royal Society Science Book Prize

Data is fundamental to the modern world. From economic development, to healthcare, to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this bias, in time, money, and often with their lives.

Celebrated feminist advocate Caroline Criado Perez investigates the shocking root cause of gender inequality and research in Invisible Women?, diving into women s lives at home, the workplace, the public square, the doctor s office, and more. Built on hundreds of studies in the US, the UK, and around the world, and written with energy, wit, and sparkling intelligence, this is a groundbreaking, unforgettable expose that will change the way you look at the world.
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Product details

  • Paperback | 432 pages
  • 140 x 210 x 35.56mm | 444.52g
  • Harry N. Abrams, Inc.
  • New York, United States
  • English
  • 1419735217
  • 9781419735219
  • 11,212

Review quote

"Even with all the progress women have made in the last few decades, Invisible Women proves we still have a long way to go. Reading this book--preferably in a comfortably warm room--is the first step."--PureWow
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About Caroline Criado Perez

Caroline Criado Perez is a writer, broadcaster, and feminist activist, named Liberty Human Rights Campaigner of the Year and OBE by the Queen. She has a degree in English language and literature from the University of Oxford, and she studied behavioral and feminist economics at the London School of Economics. She lives in London.
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Rating details

4.36 out of 5 stars
- 90,697 ratings
5 52% (47,542)
4 35% (31,578)
3 10% (9,224)
2 2% (1,673)
1 1% (680)
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