Quantifying for Qualifying: A Framework for Assessing Gender Equality in Higher Education Institutions - Josilene Aires Moreira; Catarina Sales Oliveira (Social Sciences, 2022)
The objective of this study is to present the development of a framework for assessing gender inequality in higher education institutions (HEIs) which reveals how this academic environment is progressing in terms of gender balance. It proposes a multi-dimension-based index comprised by five dimensions—Empowerment, Education, Health, Violence, and Time. The mathematical model used enables the user to assign a weight value to each dimension, customizing the results according to the institution addressed. The paper is based on a post-doctoral research project which analyzed six globally recognized indexes (Gender Inequality Index; Global Gender Gap Index; Women, Business, and Law Index; Gender Equality Index; Social Institutions Global Index; Women Empowerment Principles) to construct a new framework for gender inequality evaluation tailored for HEIs. It used a Laplace–Gauss-based scale. The research included an experiment of concrete application to two instiutions, one in Europe and the other in South America. While the first one had a Gender Equality Plan, the second had not. The analysis was successfully conducted in both institutions. The two institutions presented general results above 60%. These results need to be read in the specific context of each university. The Gender Equality in Higher Education Institutions Index (GEHEI) provides a user-friendly way of checking the existence of gender inequality, summarized into a single number but able to be detailed in several levels and to provide insight into progression over time. The handling of the GEHEI tool is also very straightforward. The proposal is designed to be used in different HEIs; it is recommended that researchers customize the weights of the dimensions according to their relevance in the specific organization. This paper provides a new methodological model to measure gender inequality in HEIs based on easy-to-obtain data, distinguishing itself from global indexes by its ease of application and interpretation.