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DGBIAS – Detecting gender bias in children's books

In this project, we propose a solution for addressing gender under- and misrepresentation in textual literature for pre- and primary-school children. The goal of the project is twofold. Firstly, we want to identify and measure different aspects related to gender under- and misrepresentation. For example, proportion of male vs. female characters, gender-assuming pronouns and language that reinforces stereotypical gender roles could all be relevant in this context. Once reliable measurements are obtained, they will be combined into a gender representation score. The score should be easily interpretable to increase public awareness and serve as an aid to parents, educators and decision-makers. Secondly, after computing this score we want to develop best-practice guidelines for its validation in order to ensure transparency and accuracy of the methodology. In this step we will rely primarily on the opinions of gender experts and linguists.


Principal Investigator: Laura Vana-Gür (TU Wien)

Team: Camilla Damian, Laura Vana-Gür


Program / Call:FWF 1000 Ideas Programme, opens an external URL in a new window

Funding: FWF Austrian Science Fund

Start: 01 December 2021, duration: 18 months