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Research has shown that even those who consider themselves gender champions fall sway to unconscious bias. For example, a recent study showed recommendation letters written to promote students’ achievements were found to value characteristics along distinctly gendered lines in their descriptions of intelligence and capacities. More @Wikipedia
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- 5 ways to improve gender equality in the workplace - The World Economic ...Gender in-equity in the workplace can be inherent in recruitment processes, particularly in male-dominated industries. Yet gender bias can lead to productivity losses of about $2.8 million a year, a recent study found. Standardized interviews and skills-based assessments can help address the issue.
- How to beat gender stereotypes: learn, speak up and reactLet’s be honest: stereotypes won’t disappear unless people understand they are harmful. Women in male-dominated environments can help raise awareness. Role models play a crucial role in promoting gender equality and fighting gender stereotypes (e.g. Billie Jean King in sport, Sheryl Sandberg’s Lean In initiative and the #banbossy campaign).
- 7 surprising and outrageous stats about gender inequalityAt the current rate of progress, it will take another 108 years to reach gender parity, according to the World Economic Forum’s most recent Global Gender Gap report. Across the 106 countries covered since the first edition of the report, the biggest gaps to close are in the economic and political empowerment dimensions, which will take 202 ...
- Gender Gap: This is the state of work for women in 2024And while there’s a way to go – at current rates, it could take five generations or 134 years to achieve gender parity worldwide, according to the World Economic Forum’s Global Gender Gap Report 2024 – there are signs of post-pandemic recovery in economies and labour markets.
- This is why AI has a gender problem | World Economic ForumMost prominently, we have seen workshops specializing on abusive language detection and the detection of sexism at the top natural language processing conference. Facebook AI has a group working on “machine integrity” issues. Google has made efforts in reducing search bias, selection bias, data bias and latent bias in machine learning.
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