The identification of Gender Bias in the U.S. Military

Abstract

Although females represent almost half of the U.S. civilian labor force, they account for less than 15 percent of the officers in the U.S. military. To account for this discrepancy, this thesis tests for gender bias within the U.S. military by analyzing unique datasets derived from Naval Postgraduate School. We first conduct a randomized control trial by means of a survey (n=234). One group responds to scenarios relating to one gender; the second group responds to the same scenarios but relating to the opposite gender. We then use statistical analysis and ordinary least squares models to compare responses between genders. Second, using NPS student evaluations of teaching (n=175,093), we conduct t tests, examine the correlation of evaluation questions on instructor effectiveness, and employ ordinary least squares models using student and course fixed effects, and instructor and course fixed effects while controlling for student, instructor, class and school characteristics to analyze how gender influences evaluations. Our results identify that students favor matched gender pairs, with the effect largest among male pairs. We found this effect to be of marginal economic significance. These findings may indicate the effectiveness of gender equality training, or may reflect the current social climate concerning gender bias.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2018
Accession Number
AD1052895

Entities

People

  • Brandon K. Wolf
  • Luke T. Siwek

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Data Analysis
  • Data Science
  • Department Of Defense
  • Discrimination
  • Distance Learning
  • Education
  • Employment
  • Enlisted Personnel
  • Families (Human)
  • Gender Discrimination
  • Human Resources
  • Information Science
  • Institutional Review Board
  • Instructors
  • Personnel Management
  • Prejudice
  • Psychology
  • Schools
  • Social Psychology
  • Statistical Analysis
  • Statistics
  • Students
  • Surveys
  • Training
  • United States

Readers

  • Computational Modeling and Simulation
  • Organizational Psychology.