This article asks, on a systemic scale, how published articles in “Slavic Studies” do and do not reflect critically on race and other cultural constructions of identity. Digital Humanities methods provide a digital bird's-eye view of over 100,000 scholarly texts, primarily in Russian and English, through three computational approaches: frequency analysis, topic modeling, and perspectival modeling. The authors demonstrate that there is an absence of critical tools for conducting research about race in our field, despite a prevalence of racialized subject matter. These results offer a data-based refutation of the common misconception that race is outside the scholarly concerns of our field. Rather, the data affirms student accounts of the field's inadequacies in grappling with race and racism, both in historical objects of study and in the world that scholars navigate. Digital methods also locate scholarship inside and outside Slavic Studies that offers positive guidance for future work.

中文翻译：

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通过数字镜头阅读斯拉夫研究奖学金中的种族

本文从系统的角度询问“斯拉夫研究”中发表的文章如何批判性地反映种族和其他文化认同结构。Digital Humanities 方法通过三种计算方法提供超过 100,000 篇学术文本的数字鸟瞰图，主要是俄语和英语：频率分析、主题建模和透视建模。作者证明，尽管种族化的主题盛行，但在我们的领域中缺乏进行种族研究的关键工具。这些结果提供了基于数据的驳斥，驳斥了普遍的误解，即种族不在我们领域的学术关注范围之内。相反，数据证实了学生对该领域在应对种族和种族主义方面的不足之处的描述，无论是在历史研究对象中，还是在学者们所驾驭的世界中。数字方法还定位斯拉夫研究内外的学术研究，为未来的工作提供积极的指导。