Gendered Agentic Language Patterns in Evaluative Text

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Differences in the way men and women are described in textual evaluations have been documented in letters of recommendation, professor evaluations, and performance evaluations. To this point, most studies have been done qualitatively. Several studies show that there are differences in the way men and women are described with agentic language, or language describing individual accomplishment with terms like execute, drive, or ambitious. These gendered differences can be consequential in terms of overall performance assessment. A recent study showed that agentic language increases with performance for men but only does so to a point for women before decreasing at the highest levels. Here, we apply computational techniques to show gendered differences in agentic language patterns hold at the scale of an entire technology company for the first time. We construct a lexicon based on relevant literature to obtain frequencies of agentic language terms in the corpus. We find that our analysis of agentic language patterns conceptually replicates a similar study’s findings using entirely new data and methods. We model the findings and find robust significance regarding a positive increase in agentic language for men rising to the top of the organization, but a decrease in agentic language in the reviews of top-performing women. We discuss the implications of a simple computational technique’s ability to capture this phenomenon. We consider potential future applications of this technique to other companies and discuss future research directions.


Type of resource text
Date created June 5, 2019


Author Schroeder, Hope


Subject gender
Subject language
Subject symbolic systems
Subject agentic
Subject computational
Subject performance
Subject evaluation
Genre Thesis

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This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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Schroeder, Hope. (2019). Gendered Agentic Language Patterns in Evaluative Text. Stanford Digital Repository. Available at:


Undergraduate Honors Theses, Symbolic Systems Program, Stanford University

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