A Rationale for the Study of Intersectional Wage Discrimination
Roger White
Chapter Chapter 1 in Intersectionality and Discrimination, 2023, pp 3-22 from Springer
Abstract:
Abstract We begin with a brief discussion of the relationship between social justice and economic justice. This is followed by a presentation of persistent differences in U.S. labor market outcomes. Specifically, we identify significant differences in unemployment rates and hourly wages across race- and sex-based classifications, respectively. We then present unadjusted wage gaps (i.e., raw differences in average hourly wage rates) for several worker groups that correspond to the non-productive personal characteristics we consider in this study. These characteristics include Hispanic ethnicity, nativity, race, and sex. Having motivated our study, we introduce intersectionality and our primary research question: Is wage discrimination intersectional? This is followed by a discussion of why we use the term “discrimination” when referring to differences in wage rates that cannot be explained by differences in workers’ productive characteristics. We conclude the chapter with a roadmap for the remainder of the book.
Keywords: Discrimination; Economic justice; Intersectionality; Multiple intersecting identities; Social justice; Wage gap (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-26125-1_1
Ordering information: This item can be ordered from
http://www.springer.com/9783031261251
DOI: 10.1007/978-3-031-26125-1_1
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().