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A Bibliometric Approach for Detecting the Gender Gap in Computer Science

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Women are underrepresented in the fields of science, technology, engineering, and mathematics (STEM) in most countries, including Germany and the U.S.29,32 This was demonstrated in several surveys investigating the proportion of women in the STEM fields for specific populations. Some of these studies, for example, investigated the number of enrolled students10,30 or the percentage of female professors at universities. Other studies analyzed the disparities in research funding.23 Nearly all these surveys selected a particular population of women in consideration of their university degree or their nationality.11,34 Like many other studies investigating the gender gap and its reasons in science, these surveys are usually based on data records from several kinds of registrations or enrollments, for example, the enrollment as student or doctoral student, the registration of finished doctoral theses or the membership as professor in a certain country.1,14,16,28 However, researchers at the postdoctoral level or industrial researchers are often not registered and unfortunately drop out of the surveys.

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Bibliometric approaches are widely used to detect the gender gap and to determine possible reasons for it,4,12,15,33 for example, the research performance or collaboration behavior1,2,4,18 or different cognitive or sociocultural determinants.9,13,16 In this study, we use a method to detect the gender gap in the group of scientifically active researchers regardless of the limitations mentioned and focused to a certain scientific field. The group of interest comprises scientists that are currently active in doing research and publishing their findings—regardless of their university degree, nationality, gender, age, or origin and irrespective of their employment level in university or industry. As a case study, we measured the gender gap in the scientific field of the Transregional Research Centre 89 Invasive Computing (CRC/Transregio 89),a which investigates a novel paradigm for the design and programming of future parallel computing systems and covers research from diverse domains of computer science and electrical engineering, such as computer engineering, operating systems, programming languages, security, robotics, and high-performance computing. To ensure only scientifically active scientists are taken into account, we decided to collect data of researchers that successfully published their results in proceedings of international conferences within the last six years.


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