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

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

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

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.

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

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 1960-1990 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

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

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

“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.

“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.

“Critical Filter” Hypothesis

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

“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.

“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.

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

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

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

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

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

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

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

Post-S/E baccalaureate career paths

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

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

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

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

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

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

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

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.

Predicted Migration Rate by Gender and Family Structure

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.”

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

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.

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

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

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)

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***

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***

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

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

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

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