Dr Siân Brooke

LSE Fellow in Computational Social Science

If men continue to dominate computing, the oppression of women will endure

Dr Siân Brooke

The Data Science Institute (DSI) is proud to work alongside the academic departments across LSE to foster the study of data science with a focus on social, economic, and political aspects.

The Department of Methodology is an example of one of these active academic departments and the Department's LSE Fellow in Computational Social Science Dr Siân Brooke is the focus of this data science spotlight.

Siân's activist research agenda combines cultural and computational methods to understand the ways in which to increase gender equity in computing. Siân outlines this research agenda below.



Challenging Gender Inequality in Programming

Dr Siân Brooke
Website | Twitter

Computing is sexist. Despite decades of work on the behalf of educators, academics and activists, the proportion of women involved in coding is declining. Even so, referring to programming as inherently and intentionally sexist remains controversial. The lack of women in technical fields has led to widespread assumptions about gendered differences in ‘natural’ ability; differences which are used to explain the variation in skill and success. Men are framed as naturally gifted programmers, with the implication that there is something incompatible about femininity and computers. The presumed meritocracy of programming culture dismisses women’s lack of participation as due to incompetence or disinterest rather than flagrant sexism. In addition, belief in this meritocracy valorises white men such as Steve Jobs or Elon Musk as computer geeks who turned their innate abilities into vast technology empires, a narrative which frequently neglects their immense privilege (or emerald mines). Beyond its heroes, the malice of meritocracy is the implication that if people are not already there it is because they do not want to be.

Entitled Trouble in Programmer’s Paradise, my most recent publication asks how sexism functions on anonymous forums. I conduct a non-binary computational analysis of gender on the worlds largest programming forum Stack Overflow. My study encompasses 11-years of activity, across levels of expertise, coding language, and specialise to assess if programming websites are hostile to women and feminine users. First, I examine individual metrics, asking if there are gender differences in key metrics of user’s success on Stack Overflow. Platform scoring systems (such as voting) are not evidence of fairness, but the functioning of established norms that can hide prejudice. Second, I test the notion that technology culture is a meritocracy. I find that whilst women and feminine users receive lower scores in evaluating their technical answers, there is convincing evidence of higher effort in their contributions, compared to anonymous and more masculine users. I conclude that women’s negative experiences in technical spaces are the result of structurally supported gender biases, not a lack of effort or knowledge. Supplementing the finds of this paper, I also develop recommendations for greater gender inclusivity on Stack Overflow.

In addition, I have also been awarded a three-year Leverhulme Early Career Research Fellowship for my project entitled Hardcoding Gender: Dismantling Gendered Differences in Collaborative Computing. Focusing on the collaborative coding platform GitHub, I will conduct two distinct but complimentary studies into (1) gender differences in python code and (2) characterising responses to sexism that are effective in preventing future hostility. Previous scholarship has shown that women are successful on programming platforms when their gender is anonymised, but are penalised, face hostility and find their contributions devalued when their gender is known. This project builds on this existing work, using computational methods to understand the experience of women moving through these modes of technical collaboration and skill building. This project will provide essential insights into gender-based prejudice in the world’s largest technical collaboration platform, working towards a more just and equal future of computing. 

My research agenda is ultimately a work of activism that combines cultural and computational methods to understand how to increase gender equity in computing. Despite its flaws, computing is our future, and it matters who builds that future. If men continue to dominate computing, the oppression of women will endure, actively and tacitly erasing women in the design of our common future. With the recent increase in online learning and remote collaboration, it is imperative that these new spaces break with the hostility, discrimination and exclusion that currently characterises programming. The computing sector desperately needs a higher proportion of women.