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Despite decades of efforts, the gender gap in pay and leadership opportunities is widening, not only in established industries but also in 'newer' fields such as Analytics and Data Science.

One of the reasons proposed for these disparities is the Confidence Gap: the idea that men typically apply for roles when they meet 60% of the job requirements while women need to meet 100% of the requirements to apply. This statistic is culturally resonant - people from around the world in all sorts of roles refer to it and a wealth of anecdotes in the world recruiting backs this observation up. However, the root cause of the Confidence Gap is understudied. There's a lot of research to suggest that women feel as confident in their skills, abilities and leadership as men. Perhaps we have mistaken the symptom (that is, women's inability to promote themselves) for the cause?

In this talk, I will discuss how our studies of the confidence gap impact candidate pools based on millions of recruiting outcomes. I describe three specific contexts where we've seen the confidence gap manifest (overqualified roles, job titles and language of job descriptions) and describe a model for the confidence gap and what that means for companies trying to recruit fairly. I also discuss what that means for individual job seekers and mechanisms they can use to overcome it.

What is tech policy and how you can get involved
What is tech policy and how you can get involved
How low (level) can you go
How low (level) can you go