July 21, 2014 magda piatkowska

Where are all my girlfriends? Why women are under-represented in tech.

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As I go through my career I can’t help but wonder: Why there are there so few women in technical jobs? In other words: where are all my girlfriends?

I don’t believe there are any differences in predisposition that are preventing women from going into tech. I do believe however that there are many barriers faced by women in this area.

It starts with the direction that is given to young children and carries on into early education. Are girls encouraged to do computer science or maths in the way that boys are? And how does this impact the number of students and graduates who take up technical studies? Then there is the problem of the workplace – research suggests that men are more confident here than women. Potentially this makes a difference too. The data suggests that family matters also have a slightly stronger impact on women than on men. This in itself should not create any challenges however it becomes an issue when we look at the benefits and support that the workplace offers. Would there be more women in tech companies if they provided a better level of social support? Finally people tend to follow role models. Are there enough highly visible female role models in technology to inspire young women and thus impact their career choices?

In order to answer some of those questions and test my thesis, I have collected publications and research (see sources below), gathered public data (see below for details) and used Twitter API to research the extent of social media influence.

Based on that I have created a visualised, interactive story.

I am using infogr.am to build an interactive visualisation. Yes, I know! Infographics are getting a bit overused and they are not as flexible and visually attractive as many JavaScript libraries. However using infogr.am is quick and easy, it is interactive and saves a lot of coding. Plus, it embeds nicely into WordPress, as you can see here:

Sources

  • Institute of Leadership & Management. Ambition and gender at work. Retrieved from here.
  • Chris Jones. (10/03/2014). Breaking through the gender barrier. Huffingtonpost.com. Retrieved from here.
  • Thea Hamren. (14/11/2013). Seriuosly, let’s do something about the 3%. Huffingtonpost.com. Retrieved from here.
  • Liz Bolshow. (14/04/2014). Employment Statistics – a gender issue?. FT.com. Retrieved from here.
  • Etzkowitz H., Kemelgor C., Neuschatz M., Uzzi B.. Barriers to Women in Academic Science and Engineering. Retrieved from here.
  • Heller M. (2012). The CIO Paradox.
  • Alvarado C., Dodds Z.. Hurvey Mudd College. Women in CS: An Evaluation of Three Promising Practises.Retrieved from here.
  • Ashcraft C., Eger E., Friend M. National Center for Women&Information Technology. (2012) Girls in IT: The Facts. Retrieved from here.
  • Klawe M. (12/2013). Harvey Mudd College. Increasing participation of women in computing careers. Retrieved from https://socialissues.cs.toronto.edu/2013/12/women/
  • Public data sourced from here. Including:
    Pension Provision (Employer) by SIC2007 Industry, Self Employed jobs by industry (UK totals), All in employment by industry sector.

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  • About the Author

    magda piatkowska I left uni as a systems engineer to take up DBA and later various BI positions at eircom in Dublin, Ireland. I then moved from telco to the gaming industry to join Silicon Valley's Zynga. I built there an international insights and analytics team. The team specialised in real time insights delivery and developing machine learning capabilities. We focused on text mining algorithms in order to include customer feedback in product development, segmentation and recommendations. I am currently with Channel4 where we are building a cutting edge data science team. Also, strongly supporting girls in rocking the world of technology!

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    Machine Learning and Analytics based in London, UK