The concept of epistemic breadth of the work of a researcher refers to the scope of their knowledge claims, as reflected in published research reports. Studies of epistemic breadth have been hampered by the lack of a validated measure of the concept. Here we introduce a knowledge space approach to the measurement of epistemic breadth and propose to use the semantic similarity network of an author's publication record to operationalize a measure. In this approach, each paper has its own location in a common abstract vector space based on its content. Proximity in knowledge space corresponds to thematic similarity of publications. Candidate measures of epistemic breadth derived from aggregate similarity values of researchers' bodies of work are tested against external validation data of researchers known to have made a major change in research topic and against self-citation data. We find that some candidate measures co-vary well with known epistemic breadth of researchers in the empirical data and can serve as valid indicators of the concept.

翻译：科研人员工作的认知广度概念指其知识主张的范围，这体现在已发表的研究报告中。由于缺乏经过验证的该概念测度方法，认知广度的研究一直受到阻碍。本文引入知识空间方法来测量认知广度，并提出利用作者发表记录的语义相似性网络来实现测度操作化。在该方法中，每篇论文基于其内容在一个共同的抽象向量空间中拥有自身的位置。知识空间中的邻近性对应着出版物的主题相似性。我们从研究人员整体工作的聚合相似度值推导出认知广度的候选测度，并针对已知在研究主题上做出重大改变的研究人员的外部验证数据以及自引数据进行检验。我们发现，某些候选测度与实证数据中已知的研究人员认知广度具有良好的协变性，可以作为该概念的有效指标。