Online labour markets (OLMs) are a vital source of income for globally diverse and dispersed freelancers. Despite their promise of neutrality, OLMs are known to perpetuate hiring discrimination, vested in how OLMs are designed and what kinds of interactions they enable between freelancers and hirers. In this study, we go beyond understanding mechanisms of hiring discrimination in OLMs, to identifying platform design features that can minimise hiring discrimination. To do so, we draw on a methodology guided by the design justice ethos. Drawing on a survey on UK-based freelancers and interviews with a purposefully drawn sub-sample, we collaboratively identify five platform design interventions to minimise hiring discrimination in OLMs: community composition, identity-signalling flairs, text only reviews, union membership, and an antidiscrimination prompt. The core of our study is an innovative experiment conducted on a purpose-built, mock OLM, Mock-Freelancer.com. On this mock OLM, we experimentally test mechanisms of discrimination, including how these mechanisms fare under the five altered platform design interventions through a discrete-choice experiment. We find that community and flairs were important in encouraging hiring women and non-White freelancers. We also establish that anonymity universally disadvantages freelancers. We conclude with recommendations to design OLMs that minimise labour market discrimination.

CITATION
Brooke, S., & Rao, A. H. (2024). Designing for justice in freelancing: Testing platform interventions to minimise discrimination in online labour markets. Big Data & Society, 11(1).

The underrepresentation of women in open-source software is frequently attributed to women’s lack of innate aptitude compared to men: natural gender differences in technical ability. Approaching code as a form of communication, I conduct a novel empirical study of gender differences in Python programming on GitHub. Based on 1,728 open-source projects, I ask if there is a gender difference in the quality and style of Python code measured in adherence to PEP-8 guidelines. I found significant gender differences in structure and how Python files are organized. While there is gendered variation in programming style, there is no evidence of gender difference in code quality. Using a Random Forest model, I show that the gender of a programmer can be predicted from the style of their Python code. The study concludes that gender differences in Python code are a matter of style, not quality.

CITATION
Brooke, S. (2024) Programmed differently? Testing for gender differences in Python programming style and quality on GitHub, Journal of Computer-Mediated Communication, 29, (1).

This paper investigates how the conceptions of gender in memes are central to socializing at hackathons. Drawing on a multi-sited ethnography of seven hackathons, I provide insight into how references to memes and informal technology culture shape interaction in local manifestations of this culture. The contribution of this paper is twofold. First, I show how vocabularies and artifacts of technology culture move between on and offline spaces. These findings have implications for HCI research that investigates questions of materiality in computer-mediated communication. Second, I show how even the mundane memes of technology culture can reveal the toxic masculinity and ideology of Incels. By tying these internet memes to a physical context, I unpack how humour can reveal and perpetuate the enduring masculine dominance of technology. I end with recommendations for increasing inclusivity at hackathons based on how HCI is uniquely positioned to understand how Internet symbols and interactions manifest offline.

CITATION
Brooke, S. (2022). Nice Guys, Virgins, and Incels: Gender in Remixing and Sharing Memes at Hackathons. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI '22). Association for Computing Machinery, USA, Article 395, 1–14.

This paper examines gender-biases on Stack Overflow, the world’s largest question-and-answer forum of programming knowledge. Employing a non-binary gender identification built on usernames, I investigate the role of gender in shaping users’ experience in technical forums. The analysis encompasses 11-years of activity, across levels of expertise, language, and specialism, to assess if Stack Overflow is really a paradise for programmers. I first examine individual users, asking if there are gender differences in key user metrics of success, focusing on reputation points, user tenure, and level of activity. Second, I test if there are gender- biases in how technical knowledge is recognised in the question- answer format of the platform. Third, using social network analysis I investigate if interaction on Stack Overflow is organised by gender. Results show that sharing and recognising technical knowledge is dictated by users’ gender, even when it is operationalised beyond a binary. I find that feminine users receive lower scores for their answers, despite exhibiting higher effort in their contributions. I also show that interaction on Stack Overflow is organised by gender. Specifically, feminine users preferentially interact with other feminine users. The findings emphasise the central role of gender in shaping interaction in technical spaces, which is a necessity for participation in the masculine-dominated forum. I conclude the study with recommendations for inclusivity in online forums.

CITATION

Brooke, S. (2021) Trouble in programmer’s paradise: gender biases in sharing and recognising technical knowledge on Stack Overflow. Information, Communication, & Society. 24, (14). 2081-2112.