Produced a matched dataset linking Honours recipients with existing Wikipedia biographies.
Created comparative charts highlighting differences in biography representation by gender and profession.
Identified strong patterns showing that women in caring professions (health, education, nursing) were less likely to have Wikipedia biographies than women in politics, the judiciary, or sport.
Outcome
Findings written up as a peer-reviewed article in Big Data & Society (July 2023).
Visualisations (R/ggplot2) included in the paper and presentation materials.
Provided a reproducible workflow for linking government recognition (Australian Honours) with Wikipedia.
Impact
Helped quantify and demonstrate the systemic invisibility of women in caring professions on Wikipedia.
Contributed to discussion on gender, recognition, and representation in digital knowledge platforms.
Cited in ongoing research around data bias and visibility in open knowledge.
Reflection
Strength: Data linking + visualisation made an abstract bias visible and easy to communicate.
Challenge: Care roles often lack the “notability markers” Wikipedia uses.
Curiosity: I noticed the angle around caring professions; that insight shaped the direction.
Collaboration: Working with academics helped translate the idea into publishable research.
Comparison of Wikipedia biography coverage by profession and gender.Relative visibility: caring professions vs public-facing roles.
