Gender/Sex Related Studies Dataset

性别/性相关研究数据集是由蒙特利尔大学的研究团队利用Dimensions数据库，通过自然语言处理和手动筛选技术构建的。该数据集包含190万篇科学文献，涵盖1668年至2023年间的文献，涉及英语、西班牙语、法语和葡萄牙语。数据集的创建过程结合了核心期刊和关键词搜索，通过BERTopic主题建模技术提取关键词，以确保覆盖广泛且减少偏见。该数据集旨在解决性别研究在跨学科领域中的方法论挑战，特别是如何在不依赖传统学科分类的情况下识别相关文献。其应用领域包括性别研究的主题分析、引用和合作动态、以及机构和区域参与的分析。

The gender/sex-related research dataset was constructed by a research team from the University of Montreal using the Dimensions database, leveraging natural language processing and manual screening technologies. This dataset comprises 1.9 million scientific publications spanning 1668 to 2023, available in English, Spanish, French and Portuguese. The dataset development process integrates core journal screening and keyword search strategies, with BERTopic topic modeling employed to extract keywords, thus ensuring broad coverage and minimizing bias. This dataset aims to address the methodological challenges faced by gender research across interdisciplinary fields, particularly how to identify relevant literature without relying on traditional disciplinary classification systems. Its application areas include thematic analysis of gender research, citation and collaboration dynamics, as well as analyses of institutional and regional participation.