TDNet Discover

This quantitative, non-experimental, cross-sectional study examined the statistical relationship between gender, race, and occupational representation within the United States information technology (IT) workforce. The purpose of the study was to determine whether demographic identity categories, specifically gender and race, were significantly associated with specific IT occupations. Using nationally representative data from the U.S. Census Bureau’s American Community Survey 5-Year Public Use Microdata Sample (2023), the analysis focused on 17 distinct IT occupations classified under the Standard Occupational Classification (SOC) system. Gender and race variables were recoded to allow for intersectional analysis, enabling the study to detect patterns of overrepresentation and underrepresentation across IT occupational categories. Chi-square tests of independence confirmed statistically significant associations between gender and IT occupation, as well as between race and IT occupation. Cramer’s V was used to assess effect sizes, revealing a moderate association for gender and a weak to moderate association for race. Post hoc analyses, including standardized residuals and Bonferroni corrections identified specific IT occupational roles where disparities were most pronounced. Results indicated that women, particularly minority women, were underrepresented in software development and network architect roles. In contrast, overrepresentation was found in analytical and supportoriented positions, highlighting patterns of occupational clustering. These findings aligned with broader structural theories of labor market inequality and supported the continued application of Critical Race Theory and intersectionality in workforce equity research. Recommendations included pursuing longitudinal research, expanding demographic variables, and incorporating organizational-level data to strengthen future equity analyses.