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Gender Gap Decomposition×Intersectionality Analysis×
ValdkondGender StudiesGender Studies
PerekondRegression modelProcess / pipeline
Tekkeaasta19731989
LoojaRonald Oaxaca & Alan BlinderKimberlé Crenshaw
TüüpRegression-based decomposition of a mean group differenceCritical qualitative analytic framework
AlgallikasOaxaca, R. (1973). Male-female wage differentials in urban labor markets. International Economic Review, 14(3), 693–709. DOI ↗Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford Law Review, 43(6), 1241–1299. DOI ↗
RööpnimetusedOaxaca-Blinder Decomposition, Blinder-Oaxaca Decomposition, Wage Gap DecompositionIntersectional Analysis, Intersectionality Framework, Intersectional Qualitative Analysis
Seotud34
KokkuvõteGender gap decomposition, most often implemented as the Oaxaca-Blinder decomposition, splits the mean difference in an outcome such as wages between men and women into a part explained by differences in measured characteristics (education, experience, occupation) and an unexplained residual part attributed to differences in how those characteristics are rewarded. Introduced independently by Ronald Oaxaca and Alan Blinder in 1973, it is the workhorse method for quantifying how much of the gender pay gap reflects composition versus differential treatment.Intersectionality analysis is a critical qualitative framework that examines how multiple social categories — such as race, gender, class, sexuality, and disability — intersect and operate together to shape lived experience, advantage, and disadvantage. Coined by legal scholar Kimberlé Crenshaw in 1989 and 1991, it rejects single-axis analysis that treats categories one at a time, insisting instead that overlapping systems of power produce qualitatively distinct positions that cannot be understood by adding the categories separately.
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ScholarGateVõrdle meetodeid: Gender Gap Decomposition · Intersectionality Analysis. Loetud 2026-06-24 aadressilt https://scholargate.app/et/compare