要約

Gender inequality in science and technology fields takes various and complex shapes, from recruitment and retention across educational levels, to job entry and advancement barriers, to pay and compensation. Although the salary gap for women in these fields is well documented, much of the relevant research has relied exclusively on mean earned wages to estimate compensation differentials by gender. This approach may underestimate the actual extent of the gender gap more than if more comprehensive measures of compensation (e.g., wages along with health insurance and retirement benefits) were used. Through a two-step cluster analysis of the 2008–2010 US Census Survey of Income and Program Participation, in this study I considered wages along with access to employer-provided health and pension benefits, as well as job characteristics such as union membership, part-time employment, and access to employer-provided training, to explore labor segmentation in the science and technology workforce. The findings reveal a pattern consistent with labor segmentation, including the presence of clusters with secondary employment characteristics (i.e., low wages, part-time employment, and lack of health insurance and pension benefits). Significantly, women were overrepresented in such clusters, as well as in part-time and contingent work arrangements more generally. The findings both support and complicate the evidence from prior research on the gender gap by illustrating the cumulative impact that measures of total compensation can have in assessing the true extent of compensation disparities between men and women and by highlighting the stratification of highly skilled labor in the new economy.