Gender bias in education gained considerable relevance in the literature over the years. However, while the problem of gender bias in education has been widely addressed from a student perspective, it is still not fully analysed from an academic point of view. In this work, we study the problem of gender bias in academic promotions (i.e., from Researcher to Associated Professor and from Associated to Full Professor) in the informatics (INF) and software engineering (SE) Italian communities. In particular, we first conduct a literature review to assess how the problem of gender bias in academia has been addressed so far. Next, we describe a process to collect and preprocess the INF and SE data needed to analyse gender bias in Italian academic promotions. Subsequently, we apply a formal bias metric to these data to assess the amount of bias and look at its variation over time. From the conducted analysis, we observe how the SE community presents a higher bias in promotions to Associate Professors and a smaller bias in promotions to Full Professors compared to the overall INF community.

翻译：教育领域中的性别偏见问题多年来在文献中获得了显著关注。然而，尽管从学生视角出发的性别偏见问题已得到广泛研究，从学术角度出发的全面分析仍显不足。本研究考察了意大利信息学与软件工程学术群体中学术晋升（即从研究员晋升为副教授、从副教授晋升为正教授）过程中存在的性别偏见问题。具体而言，我们首先通过文献综述评估当前学术界对性别偏见问题的研究现状；其次，构建了一套用于收集及预处理意大利学术晋升中性别偏见分析所需INF与SE领域数据的流程；随后，采用形式化偏见度量指标评估数据中的偏见程度及其随时间的变化趋势。分析结果表明，与整体INF学术群体相比，SE学术群体在副教授晋升环节呈现更高水平的性别偏见，但在正教授晋升环节的偏见程度则相对较低。