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Describing occupational segregation in sparse and incomplete arrays

Research output: Contribution to journalArticlepeer-review

Abstract

The study of sex segregation is increasingly based on log-multiplicative and related models that allow analysts to characterize the amount and structure of segregation independently of (a) the mix of occupations in the economy and (b) the relative size of the male and female labor forces. Although these models are elegant and powerful, methodological complications can arise when the segregation arrays are sparse and small occupations frequently show up as perfectly segregated (i.e., all male or all female). The authors develop a general approach that makes it possible to analyze such sparse arrays with log-multiplicative and related models.

Original languageEnglish
Pages (from-to)554-572
Number of pages19
JournalSociological Methods and Research
Volume34
Issue number4
DOIs
StatePublished - May 2006
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 5 - Gender Equality
    SDG 5 Gender Equality
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Keywords

  • Log-multiplicative model
  • Missing data
  • Sampling zeros
  • Sex segregation

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Sociology and Political Science

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