论文标题
高等教育的不必要进步:通过文本挖掘发现学术界的性骚扰经历
Unwanted Advances in Higher Education: Uncovering Sexual Harassment Experiences in Academia with Text Mining
论文作者
论文摘要
学术界的性骚扰通常是一个隐藏的问题,因为受害者通常不愿报告他们的经历。最近,开发了一项网络调查,以提供一个机会,可以在学术界分享数千种性骚扰经历。使用有效的方法,这项研究收集并调查了2,000多次性骚扰经历,以更好地了解这些高等教育中的不良进步。本文利用文本挖掘来披露隐藏的主题,并探索其在三个变量中的体重:骚扰性别,机构类型和受害者的研究领域。我们绘制了从性骚扰文献中提取的五个主题的主题,发现超过50%的主题被分配给了不需要的性关注主题。 14%的主题是性别骚扰主题,其中侮辱性,性别歧视或贬低的评论或行为是针对妇女的。涉及性胁迫的主题中有5%(为换取性爱而提供了益处),涉及性别歧视的5%,以及7%的主题讨论了对受害者报告骚扰或根本不遵守骚扰者的报复。调查结果突出了教师和学生之间的力量差异,以及教授滥用权力时对学生的损失。尽管一些主题确实根据机构类型而有所不同,但基于骚扰者或研究领域的性别的主题之间没有差异。这项研究可能对研究人员进一步研究本文的数据集,以及对改善现有政策以在学术界创造安全和支持性环境的决策者。
Sexual harassment in academia is often a hidden problem because victims are usually reluctant to report their experiences. Recently, a web survey was developed to provide an opportunity to share thousands of sexual harassment experiences in academia. Using an efficient approach, this study collected and investigated more than 2,000 sexual harassment experiences to better understand these unwanted advances in higher education. This paper utilized text mining to disclose hidden topics and explore their weight across three variables: harasser gender, institution type, and victim's field of study. We mapped the topics on five themes drawn from the sexual harassment literature and found that more than 50% of the topics were assigned to the unwanted sexual attention theme. Fourteen percent of the topics were in the gender harassment theme, in which insulting, sexist, or degrading comments or behavior was directed towards women. Five percent of the topics involved sexual coercion (a benefit is offered in exchange for sexual favors), 5% involved sex discrimination, and 7% of the topics discussed retaliation against the victim for reporting the harassment, or for simply not complying with the harasser. Findings highlight the power differential between faculty and students, and the toll on students when professors abuse their power. While some topics did differ based on type of institution, there were no differences between the topics based on gender of harasser or field of study. This research can be beneficial to researchers in further investigation of this paper's dataset, and to policymakers in improving existing policies to create a safe and supportive environment in academia.