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Women's Representation in 60 Occupations from 1972 to 2010: More Women in High-Status Jobs, Few Women in Things-Oriented Jobs

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  • Richard A Lippa
  • Kathleen Preston
  • John Penner

Abstract

To explore factors associated with occupational sex segregation in the United States over the past four decades, we analyzed U.S. Bureau of Labor Statistics data for the percent of women employed in 60 varied occupations from 1972 to 2010. Occupations were assessed on status, people-things orientation, and data-ideas orientation. Multilevel linear modeling (MLM) analyses showed that women increasingly entered high-status occupations from 1972 to 2010, but women's participation in things-oriented occupations (e.g., STEM fields and mechanical and construction trades) remained low and relatively stable. Occupations' data-ideas orientation was not consistently related to sex segregation. Because of women's increased participation in high-status occupations, occupational status became an increasingly weak predictor of women's participation rates in occupations, whereas occupations' people-things orientation became an increasingly strong predictor over time. These findings are discussed in relation to theories of occupational sex segregation and social policies to reduce occupational sex segregation.

Suggested Citation

  • Richard A Lippa & Kathleen Preston & John Penner, 2014. "Women's Representation in 60 Occupations from 1972 to 2010: More Women in High-Status Jobs, Few Women in Things-Oriented Jobs," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
    • Handle: RePEc:plo:pone00:0095960
    DOI: 10.1371/journal.pone.0095960
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    Cited by:

    1. Andrea C Vial & Janine Bosak & Patrick C Flood & John F Dovidio, 2021. "Individual variation in role construal predicts responses to third-party biases in hiring contexts," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-28, February.
    2. Hajibabaei, Anahita & Schiffauerova, Andrea & Ebadi, Ashkan, 2022. "Gender-specific patterns in the artificial intelligence scientific ecosystem," Journal of Informetrics, Elsevier, vol. 16(2).
    3. Stephan HUMPERT, 2015. "Gender-based Segregation before and after the Great Recession," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(605), W), pages 53-62, Winter.
    4. Otterbring, Tobias & Bhatnagar, Roopali & Samuelsson, Peter & Borau, Sylvie, 2021. "Positive gender congruency effects on shopper responses: Field evidence from a gender egalitarian culture," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    5. Thelwall, Mike & Bailey, Carol & Tobin, Catherine & Bradshaw, Noel-Ann, 2019. "Gender differences in research areas, methods and topics: Can people and thing orientations explain the results?," Journal of Informetrics, Elsevier, vol. 13(1), pages 149-169.
    6. Rammohan, Anu & Goli, Srinivas & Reddy, Bheemeshwar, 2017. "Occupational Segregation by Caste and Gender in India," MPRA Paper 101969, University Library of Munich, Germany.
    7. Gijsbert Stoet & Drew H Bailey & Alex M Moore & David C Geary, 2016. "Countries with Higher Levels of Gender Equality Show Larger National Sex Differences in Mathematics Anxiety and Relatively Lower Parental Mathematics Valuation for Girls," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-24, April.

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