Machines are getting smarter. They have reached the point where they learn by themselves and make their own decisions. The consequences can be downright
As the 2010’s draw to a close, it’s worth taking a look back at the monumental progress that has been made in Deep Learning in this decade.[1] Driven by the development of ever-more powerful comput
Gender inequality has been deemed the “greatest human rights challenge of our time” by the United Nations, and scholars across numerous disciplines agree that gender stereotypes represent a primary way by which this inequality is maintained. Yet changing stereotypes in a systemic, enduring way is extremely difficult. This is at least in part because stereotypes are transmitted and perpetuated through the language societies and organizations use to describe women, especially those in leadership roles. Here, we show that hiring women into leadership positions is associated with organizations characterizing women in more leadership-congruent, agentic ways. This shift mitigates a critical barrier to women’s progression in organizations and society: the incongruence of what it means to be a woman and a leader.
We have deposited the numeric data (cosine similarities) and code used to recover the results of Study 1 publicly in an Open Science Framework repository (<https://osf.io/ut
Word Embeddings lena-voita.github.io - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from lena-voita.github.io Daily Mail and Mail on Sunday newspapers.