1. Sociological Aspects of S/E Career Participation
Yu Xie
University of Michigan
&
Kimberlee A. Shauman
University of California-Davis

2. Presentation Outline Design of study
Participation in the S/E Education
Participation in the S/E Labor force
Summary of evidence regarding common explanations for women’s underrepresentation

3. WOMEN IN SCIENCE: Career Processes and Outcomes
Yu Xie
University of Michigan
&
Kimberlee A. Shauman
University of California-Davis

4. Main Features of the Study
We take a life course approach.
We study the entirety of a career trajectory.
We analyzed seventeen large, nationally representative datasets.

5. The Life Course Approach
Interactive effects across multiple levels.
Interactive effects across multiple domains: education, family, and work.
Individual-level variation in career tracks
The cumulative nature of the life course

6. Synthetic cohort life course, outcomes examined and data sources
Chapter 4:
Gender differences in the attainment of a science/engineering bachelor’s degree
Data Source:
HSBSo
Chapter 5:
Beyond the science baccalaureate: gender differences in career paths after degree attainment
Data Sources:
NES, B&B
Chapter 6:
Gender differences in career paths
after attainment
of a master’s degree in S/E
NES
Chapter 7:
Demographic and labor force profiles of men and women in science and
engineering
Census PUMS,
SSE
Chapter 8:
Geographic mobility of men and women in science and engineering
1990 Census PUMS
Chapter 9:
The research productivity puzzle revisited
Carnegie-1969,
ACE-1973, NSPF-1988,
NSPF-1993
Chapter 10:
Immigrant women scientists/
engineers
1990 Census PUMS,
Chapter 2:
Gender differences in math and science achievement
NLS-72, HSBSr, HSBSo, LSAY1, LSAY2, NELS
Chapter 3:
Gender differences in the expectation of an S/E college major among high school seniors
NELS
High school diploma + 6 years
S/E Bachelor’s Degree + 2 years
S/E Master’s Degree + 2 years
Post-M.S. and Post-Ph.D. Career Years
Grades 7 – 12

7. Participation in S/E Secondary Education
“Critical Filter” Hypothesis
Women are handicapped by deficits in high school mathematics training
Coursework Hypothesis
Girls fail to participate in the math and science college preparatory courses during high school

8. “Critical Filter” Hypothesis
The gender gap in average mathematics achievement is small and has been declining.

9. “Critical Filter” Hypothesis
The gender gap in average mathematics achievement is small and has been declining.
The gender gap in representation among top achievers remains significant.

10. “Critical Filter” Hypothesis
The gender gap in average mathematics achievement is small and has been declining.
The gender gap in representation among top achievers remains significant.
Gender differences in neither average nor high achievement in mathematics explain gender differences in the likelihood of majoring in S/E fields.

11. “Critical Filter” Hypothesis

12. “Coursework Hypothesis”
Girls are as likely as boys to take math and science courses (except for physics).

13. “Coursework Hypothesis”
Girls are as likely as boys to take math and science courses (except for physics).
Girls attain significantly better grades in high school coursework.

14. “Coursework Hypothesis”
Girls are as likely as boys to take math and science courses (except for physics).
Girls attain significantly better grades in high school coursework.
Course participation does not explain gender differences in math and science achievement scores.

15. Participation in S/E Postsecondary Education
Representation of women among bachelors degree recipients has increased in almost all S/E fields

16. Participation in S/E Postsecondary Education
Representation of women among bachelors degree recipients has increased in almost all S/E fields
Participation gaps are greatest at the transition from high school to college:
Women are less likely to expect a S/E major
Attrition from the S/E educational trajectory is greater for women than men at the transition from high school to college

17. Sex-specific probabilities for selected pathways to an S/E baccalaureate

18. Sex-specific probabilities for selected pathways to an S/E baccalaureate

19. Participation in S/E Postsecondary Education
After the transition to college, there are no gender differences in persistence

20. Sex-specific probabilities for selected pathways to an S/E baccalaureate

21. Participation in S/E Postsecondary Education
After the transition to college, there are no gender differences in persistence
Most female S/E baccalaureates had expected to pursue non-S/E majors but shifted to S/E after entering college

22. Post-S/E baccalaureate career paths

23. Post-S/E baccalaureate career paths
Women are more likely than men to “drop out” of education and labor force participation
Among those who do not “drop out” of education and the labor force:
Women and men are equally likely to make the transition to either graduate education or work
But within either trajectory, women are significantly less likely to pursue the S/E path

24. Post-S/E baccalaureate career paths
Female-to-Male Odds Ratios of Career Transitions
Bachelor’s
Degree in S/E
1.06
0.94
0.41***
0.45***
2.44***
Graduate
Work
Studies
Graduate
No Graduate
Graduate
Working in
Working in
School in
School, Not
School in S/E
S/E
Non -
S/E
Non -
S/E
Working

25. Participation in the S/E labor force
The representation of women in the S/E labor force has increased for all fields, but gaps persist

26. Participation in the S/E labor force
The representation of women in the S/E labor force has increased for all fields, but gaps persist
Women scientists and engineers are less likely to be employed full time.
Percent employed full time, 1990:
Women scientists: 90.9
Men scientists: 96.5

27. Achievement in the S/E labor force
Women earn significantly less than men

28. Achievement in the S/E labor force
Women earn significantly less than men
Women are promoted at a significantly lower rate

29. Explanations for gaps in participation and achievement in the S/E labor force
Women are not as geographically mobile as men
Women publish at slower rates
Women’s family roles hamper their career progress

30. Are Women’s Rates of Geographic Mobility Limited?
This may be true because women are more likely than men to be in dual-career families.
However, we find
Scientists in dual-career families do not have lower mobility rates.
There are no overall gender differences across types of families.
Only married women with children have lower mobility rates.

31. Predicted Migration Rate by Gender and Family Structure

32. The “Productivity Puzzle”
Cole and Zuckerman (1984) stated: “women published slightly more than half (57%) as many papers as men.”
Long (1992 ) reaffirms: “none of these explanations has been very successful.”

33. The “Productivity Puzzle”
Sex differences in research productivity declined between 1960s and 1990s.
Trend in Female-Male Ratio of Publication Rate

34. The “Productivity Puzzle”
Sex differences in research productivity declined between 1960s and 1990s.
Most of the observed sex differences in research productivity can be attributed to sex differences in background characteristics, employment positions and resources, and marital status.

35. The “Productivity Puzzle”
Estimated Female-to-Male Ratio of Publication
Model description
1969
1973
1988
1993
(0): Sex
0.580***
0.632***
0.695**
0.817
(1): (0) + Field + Time for Ph.D. + Experience
0.630***
0.663***
0.800
0.789*
(2):(1)+Institution + Rank +Teaching + Funding + RA
0.952
0.936
0.775
0.931
(3): (2) + Family/Marital Status
0.997
0.971
0.801
0.944

36. Does a Family Life Hamper Women Scientists’ Careers?
Marriage per se does not seem to matter much.
Married women are disadvantaged only if they have children:
less likely to pursue careers in science and engineering after the completion of S/E education
less likely to be in the labor force or employed
less likely to be promoted
and less likely to be geographically mobile

37. Does a Family Life Hamper Women Scientists’ Careers?
Post-S/E baccalaureate career paths
Bachelor's
Degree in S/E
Graduate Studies
Working
Grad in
Working in
No Grad,
Grad in S/E
Working in S/E
Non-S/E
Non-S/E
Not Working
(State 1)
(State 3)
(State 2)
(State 4)
(State 5)

38. Does a Family Life Hamper Women Scientists’ Careers?
Female-to-male odds ratio of post-baccalaureate career paths by family status
Family Status
Grad school or work
Grad school
Grad School in S/E
Work in S/E
Single
0.90
1.02
0.77
0.78**
Married without children
0.28***
0.67
0.11**
0.72**
Married with children
0.05***
0.35*
0.39***

39. Female-to-Male Ratio in Labor Force Outcomes by Family Status
Does a Family Life Hamper Women Scientists’ Careers?
Female-to-Male Ratio in Labor Force Outcomes by Family Status
Family Status
Odds of employment
Earnings rate
Odds of promotion
Single
2.093***
0.929***
1.118
Married without children
0.560***
0.864***
0.985
Married with children
0.406***
0.857***
0.241***

40. Summary: What are the causes of the persistent inequities in science?
Common explanations not supported
“Critical Filter” Hypothesis
Coursework Hypothesis
Explanations supported
Supply problem
Segregation
Familial gender roles

41. Supply problem
Interest in science is relatively low among girls and young women
Expectation of an S/E college major
Participation in S/E during college
Women are significantly less likely to utilize S/E human capital
Achievement
Post-baccalaureate pursuit of S/E
Transition to the S/E labor force

42. Segregation
Women and men are segregated within science by field and by employment setting
Women are most likely to be in the biological sciences; Men are most likely to be in engineering
Gender gaps in transition to the S/E labor force and earnings
Women employed in teaching colleges; Men more likely employed in research universities
Gender gaps in publication productivity and earnings

43. Familial gender roles Marriage per se does not seem to matter much.
Married women are disadvantaged only when they have children:
less likely to pursue S/E careers after the completion of S/E education
less likely to be in the labor force or employed full time
less likely to be promoted
and less likely to be geographically mobile