Access Type
Open Access Dissertation
Date of Award
January 2024
Degree Type
Dissertation
Degree Name
Ph.D.
Department
Psychology
First Advisor
Marcus Dickson
Second Advisor
Andrew Speer
Abstract
This study employs a multi-trait, multi-method approach to investigate gender bias in leadership development evaluations in an organizational setting by combining traditional quantitative analyses with natural language processing (NLP) methodologies. Specifically, analysis of 360-degree ratings of leader competency revealed a null effect of leader gender on ratings of Agency and Communion when controlling for leader level, leader work region, rater gender, and rater source. These secondary variables, with the exception of rater gender, demonstrated small yet significant effects on competency ratings. Moreover, dictionary-based NLP and structural topic modeling analyses on narrative developmental feedback comments revealed minimal gender differences in feedback evaluations for hypothesized themes, except for feedback themes related to strategy. In this feedback, male leaders were perceived as being stronger strategic thinkers compared to female leaders, albeit with limited practical significance. Contrary to established literature on gender bias, these results underscore the importance of a nuanced approach to analyzing and understanding how intricate gender dynamics influence leadership evaluations.
Recommended Citation
Schwendeman, Michael, "Navigating The Labyrinth: An Analysis Of Gender Bias In Leadership Development Using Natural Language Processing" (2024). Wayne State University Dissertations. 4002.
https://digitalcommons.wayne.edu/oa_dissertations/4002
