we’re proud to announce that our Board member Paola Belingheri, WIA-E Director of research, has been awarded a grant for a research on Gender Bias.
Paola Belingheri is the Principal Investigator of the research project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Aerospace Industry” which has been awarded a grant by the School of Engineering of the University of Pisa, Italy.
Language can often be considered gender-specific. Adjectives, prefixes and suffixes ascribe certain genders to objects and this in turn causes people to associate them with male or female characteristics, shaping the way we examine and respond to the world around us. Moreover different words are differently interpreted by men and women and, especially in the workplace, this can lead to biases in application and recruitment processes. Although over the years much overt reference to a specific gender has been eliminated from these texts, more subtle nuances persist in the way a company presents itself, as well as the way it writes vacancy notices, which may still influence what type of person responds, including their gender. These biases are often difficult to identify by those who are operating in the field since they can be hidden in the orthographical, grammatical or semantical content of the text. This introduces a barrier for women to access male-dominated industries (e.g., space), and the business context in general. At the same time, the use of a gendered language may negatively affect the firm from a reputational point of view, as well as discourage valuable female candidates from applying for specific jobs. Using methods and tools of Text Mining and Semantic and Social Network Analysis, this research project has the objective to present a novel approach to evaluate and address the above-mentioned problems. The final outcome of the project will be a tool to identify gender bias in text documents.
The grant will be used to coordinate the work of the research team and to create a first prototype of an online gender bias analysis tool.