Women’s Work Pathways Across the Life Course

Abstract

Despite numerous changes in women’s employment in the latter half of the twentieth century, women’s employment continues to be uneven and stalled. Drawing from data on women’s weekly work hours in the National Longitudinal Survey of Youth (NLSY79), we identify significant inequality in women’s labor force experiences across adulthood. We find two pathways of stable full-time work for women, three pathways of part-time employment, and a pathway of unpaid labor. A majority of women follow one of the two full-time work pathways, while fewer than 10 % follow a pathway of unpaid labor. Our findings provide evidence of the lasting influence of work–family conflict and early socioeconomic advantages and disadvantages on women’s work pathways. Indeed, race, poverty, educational attainment, and early family characteristics significantly shaped women’s work careers. Work–family opportunities and constraints also were related to women’s work hours, as were a woman’s gendered beliefs and expectations. We conclude that women’s employment pathways are a product of both their resources and changing social environment as well as individual agency. Significantly, we point to social stratification, gender ideologies, and work–family constraints, all working in concert, as key explanations for how women are “tracked” onto work pathways from an early age.

This is a preview of subscription content, access via your institution.

Fig. 1

Notes

  1. 1.

    See https://www.nlsinfo.org/content/cohorts/nlsy79/topical-guide/employment/work-history-data and https://www.nlsinfo.org/content/cohorts/nlsy79/other-documentation/codebook-supplement/nlsy79-appendix-18-work-history-data#varcodes for more information.

  2. 2.

    The created Work History files have the same variables calculated “since the last interview,” but we use the calendar year variables to match interview year with year of age. Because of the low attrition in the NLSY, this excludes very little employment data.

  3. 3.

    Work hours are topcoded at 80+ hours per week to aid in model convergence. Less than 1 % of women worked more than 80 hours per week at a main job at each wave. Results do not change when work hours remain continuous, but some models do not achieve convergence.

  4. 4.

    Individuals are assigned to groups with varying probabilities of placement. As such, descriptive statistics by group are not precise unless they are weighted to adjust for each individual’s probability of correct placement (Nagin 2005:91). Thus, we do not provide descriptive statistics according to pathways of workforce participation, but they are available upon request.

  5. 5.

    To construct county-level unemployment rates during young adulthood, we use the Integrated Public Use Microdata Series (IPUMS) versions of the Current Population Survey from 1979–1984 (King et al. 2010) and historical Bureau of Labor Statistics (BLS) reports of employment status by state and county. We merge these data with the restricted NLSY79 Geocode data identifying respondents’ states and counties of residence at each interview to calculate variables for women’s labor market opportunities between ages 19 and 22.

  6. 6.

    Strully (2009) argued that job loss and unemployment should be measured as two distinct experiences.

References

  1. Alon, S., & Haberfeld, Y. (2007). Labor force attachment and the evolving wage gap between white, black, and Hispanic young women. Work and Occupations, 34, 369–398.

    Article  Google Scholar 

  2. Bettie, J. (2003). Women without class: Girls, race, and identity. Berkeley: University of California Press.

    Google Scholar 

  3. Bianchi, S. M., Robinson, J. P., & Milkie, M. A. (2006). Changing rhythms of American family life. New York, NY: Russell Sage Foundation.

    Google Scholar 

  4. Blair-Loy, M. (2003). Competing devotions: Career and family among women executives. Cambridge, MA: Harvard University Press.

    Google Scholar 

  5. Boushey, H. (2008). “Opting out?” The effect of children on women’s employment in the United States. Feminist Economics, 14(1), 1–36.

    Article  Google Scholar 

  6. Bratter, J. L., & Damaske, S. (2013). Poverty at a racial crossroads: Poverty among multiracial children of single mothers. Journal of Marriage and Family, 75, 486–502.

    Article  Google Scholar 

  7. Cha, Y. (2010). Reinforcing separate spheres. American Sociological Review, 75, 303–329.

    Article  Google Scholar 

  8. Cha, Y. (2013). Overwork and the persistence of gender segregation in occupations. Gender and Society, 27, 158–184.

    Article  Google Scholar 

  9. Coleman, M. T., & Pencavel, J. (1993). Trends in market work behavior of women since 1940. Industrial & Labor Relations Review, 46, 653–676.

    Article  Google Scholar 

  10. Correll, S. J. (2004). Constraints into preferences: Gender, status, and emerging career aspirations. American Sociological Review, 69, 93–113.

    Article  Google Scholar 

  11. Damaske, S. (2011). For the family? How class and gender shape women’s work. New York, NY: Oxford University Press.

    Google Scholar 

  12. Dannefer, D. (1987). Aging as intracohort differentiation: Accentuation, the Matthew effect, and the life course. Sociological Forum, 2, 211–236.

    Article  Google Scholar 

  13. Dannefer, D. (2003). Cumulative advantage/disadvantage and the life course: Cross-fertilizing age and social science theory. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 58, S327–S337.

  14. Domina, T., & Roksa, J. (2012). Should mom go back to school? Post-natal educational attainment and parenting practices. Social Science Research, 41, 695–708.

    Article  Google Scholar 

  15. Elder, G. H., Jr. (1998). The life course as developmental theory. Child Development, 69, 1–12.

    Article  Google Scholar 

  16. England, P. (2010). The gender revolution: Uneven and stalled. Gender and Society, 24, 149–166.

    Article  Google Scholar 

  17. England, P., Ross, M., & Garcia-Beaulieu, C. (2004). Women’s employment among blacks, white and three groups of Latinas: Do more privileged women have higher employment? Gender and Society, 18, 494–509.

    Article  Google Scholar 

  18. Folbre, N. (2001). The invisible heart: Economics and family values. New York, NY: New Press.

    Google Scholar 

  19. Frech, A., & Damaske, S. (2012). The relationships between mothers’ work pathways and physical and mental health. Journal of Health and Social Behavior, 53, 396–412.

    Article  Google Scholar 

  20. Gerson, K. (1985). Hard choices: How women decide about work, career, and motherhood. Berkeley: University of California Press.

    Google Scholar 

  21. Hibbard, J. H., & Pope, C. R. (1993). Health effects of discontinuities in female employment and marital status. Social Science & Medicine, 36, 1099–1104.

    Article  Google Scholar 

  22. Hoffman, S. D., & Maynard, R. A. (2008). The consequences of teenage childbearing on the mother and their spouse. Washington, DC: Urban Institute.

    Google Scholar 

  23. Hostetler, A. J., Sweet, S., & Moen, P. (2007). Gendered career paths: A life course perspective on returning to school. Sex Roles, 56(1–2), 85–103.

    Article  Google Scholar 

  24. Hout, M., Levanon, A., & Cumberworth, E. (2011). Job loss and unemployment. In D. B. Grusky, B. Western, & C. Wimer (Eds.), The great recession (pp. 59–81). New York, NY: Russell Sage Foundation.

    Google Scholar 

  25. Hynes, K., & Clarkberg, M. (2005). Women’s employment patterns during early parenthood: A group-based trajectory analysis. Journal of Marriage and Family, 67, 222–239.

    Article  Google Scholar 

  26. Jacobs, J. A. (1989). Revolving doors: Sex segregation and women’s careers. Stanford, CA: Stanford University Press.

    Google Scholar 

  27. Jones, B. L., & Nagin, D. S. (2013). A note on a Stata plugin for estimating group-based trajectory models. Sociological Methods & Research, 42, 608–613.

    Article  Google Scholar 

  28. King, M., Ruggles, S., Alexander, J. T., Flood, S., Genadek, K., Schroeder, M. B., . . . Vick, R. (2010). Integrated Public Use Microdata Series, Current Population Survey: Version 3.0 [Machine-readable database]. Minneapolis: Minnesota Population Center [producer and distributor].

  29. Klerman, J. A., & Leibowitz, A. (1994). The work-employment distinction among new mothers. Journal of Human Resources, 29, 277–303.

    Article  Google Scholar 

  30. Lerman, R., & Schmidt, S. (1999). An overview of economic, social, and demographic trends: Introduction. Washington, DC: Urban Institute.

    Google Scholar 

  31. McCall, L. (2001). Complex inequality: Gender, class and race in the new economy. New York, NY: Routledge.

    Google Scholar 

  32. McClendon, D., Kuo, J. C.-L., & Raley, R. K. (2014). Opportunities to meet: Occupational education and marriage formation in young adulthood. Demography, 51, 1319–1344.

    Article  Google Scholar 

  33. McLanahan, S., & Percheski, C. (2008). Family structure and the reproduction of inequalities. Annual Review of Sociology, 34, 257–276.

    Article  Google Scholar 

  34. Milgrom, E. M., & Petersen, T. (2006). The glass ceiling in the United States and Sweden: Lessons from the family-friendly corner of the world, 1970 to 1990. In F. D. Blau, M. C. Brinton, & D. B. Grusky (Eds.), The declining significance of gender? (pp. 156–211). New York, NY: Russell Sage Foundation.

    Google Scholar 

  35. Mirowsky, J. (1999). Analyzing associations between mental health and social circumstances. In C. S. Aneshensel & J. C. Phelan (Eds.), Handbook of the sociology of mental health (pp. 105–124). New York, NY: Springer.

    Google Scholar 

  36. Moen, P. (2001). The gendered life course. In L. George & R. Binstock (Eds.), Handbook of aging and the social sciences (pp. 179–196). San Diego, CA: Academic Press.

    Google Scholar 

  37. Moen, P., Dempster-McClain, D., & Williams, R. M., Jr. (1992). Successful aging: A life-course perspective on women’s multiple roles and health. American Journal of Sociology, 97, 1612–1638.

    Article  Google Scholar 

  38. Moen, P., & Han, S.-K. (2001). Gendered careers: A life-course perspective. In R. Hertz & N. Marshall (Eds.), Working families: The transformation of the American home (pp. 42–57). Berkeley: University of California Press.

    Google Scholar 

  39. Nagin, D. (2005). Group-based modeling of development. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  40. Nelson, M. K., & Smith, J. (1999). Working hard and making do. Berkeley: University of California Press.

    Google Scholar 

  41. O’Rand, A. M. (2006). Stratification and the life course: Life course capital, life course risks, and social inequality. In R. Binstock & L. George (Eds.), Handbook of aging and the social sciences (pp. 145–162). New York, NY: Academic Press.

    Google Scholar 

  42. Pavalko, E. K., & Smith, B. (1999). The rhythm of work: Health effects of women’s work dynamics. Social Forces, 77, 1141–1162.

    Article  Google Scholar 

  43. Percheski, C. (2008). Opting out? Cohort differences in professional women’s employment rates from 1960 to 2005. American Sociological Review, 73, 497–517.

    Article  Google Scholar 

  44. Reid, L. L., & Padavic, I. (2005). Employment exits and the race gap in young women’s employment. Social Science Quarterly, 86, 1242–1260.

    Article  Google Scholar 

  45. Ridgeway, C. L., & Correll, S. J. (2004). Unpacking the gender system: A theoretical perspective on gender beliefs and social relations. Gender and Society, 18, 510–531.

    Article  Google Scholar 

  46. Risman, B. J. (1998). Gender vertigo: American families in transition. New Haven, CT: Yale University Press.

    Google Scholar 

  47. Shafer, E. F. (2011). Wives’ relative wages, husbands’ paid work hours, and wives’ labor-force exit. Journal of Marriage and Family, 73, 250–263.

    Article  Google Scholar 

  48. Stone, P. (2007). Opting out? Why women really quit careers and head home. Berkeley: University of California Press.

    Google Scholar 

  49. Strully, K. W. (2009). Job loss and health in the U.S. labor market. Demography, 46, 221–246.

    Article  Google Scholar 

  50. U.S. Bureau of Labor Statistics. (2009). Employment and earnings, 2009 annual averages and the monthly labor review. Washington, DC: U.S. Department of Labor.

    Google Scholar 

  51. Vespa, J. (2009). Gender ideology construction: A life course and intersectional approach. Gender and Society, 23, 363–387.

    Article  Google Scholar 

  52. Von Hippel, P. T. (2007). Regression with missing Ys: An improved strategy for analyzing multiply imputed data. Sociological Methodology, 37, 83–117.

    Article  Google Scholar 

  53. Webber, G., & Williams, C. (2008). Mothers in “good” and “bad” part-time jobs: Different problems, same results. Gender and Society, 22, 752–777.

    Article  Google Scholar 

  54. Williams, S., & Han, S.-K. (2003). Career clocks: Forked roads. In P. Moen (Ed.), It’s about time: Couples and careers (pp. 80–97). Ithaca, NY: ILR Press.

    Google Scholar 

  55. Willis, P. E. (1977). Learning to labor: How working class kids get working class jobs. New York, NY: Columbia University Press.

    Google Scholar 

  56. Willson, A. E., Shuey, K. M., & Elder, G. H., Jr. (2007). Cumulative advantage processes as mechanisms of inequality in life course health. American Journal of Sociology, 112, 1886–1924.

    Article  Google Scholar 

Download references

Acknowledgments

Both authors contributed equally to the article. We deeply appreciate the critical feedback from the Demography Editor and reviewer, and also the thoughtful comments on the revision from Gordon De Jong and Michelle Frisco. We also thank Jamie Lynch, Bobby Jones, Natasha Sarkisian, Kristen Schultz Lee, Heather Jacobson, Richard Petts, and Emily Greenman for their helpful comments and critiques on earlier drafts of this article. We acknowledge assistance provided by the Population Research Institute at Penn State University, which is supported by an infrastructure grant by the National Institutes of Health (2R24HD041025-11). This research was conducted with restricted access to Bureau of Labor Statistics (BLS) data. The views expressed here do not necessarily reflect the views of the BLS.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Sarah Damaske.

Appendix

Appendix

Table 5 Average posterior probabilities of group assignment and Bayesian Information Criterion (BIC) statistics of model fit for women's pathways of work hours

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Damaske, S., Frech, A. Women’s Work Pathways Across the Life Course. Demography 53, 365–391 (2016). https://doi.org/10.1007/s13524-016-0464-z

Download citation

Keywords

  • Workforce participation
  • Gender
  • Life course
  • Socioeconomic status
  • Work–family