Sociological Aspects of S/E Career Participation

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Sociological Aspects of S/E Career Participation

• Yu Xie
• University of Michigan
• Kimberlee A. Shauman
• University of California-Davis

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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 womens underrepresentation

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

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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

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Synthetic cohort life course, outcomes examined
and data sources
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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

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Critical Filter Hypothesis

• The gender gap in average mathematics achievement
  is small and has been declining.

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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.

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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.

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Critical Filter Hypothesis
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Coursework Hypothesis

• Girls are as likely as boys to take math and
  science courses (except for physics).

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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.

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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.

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Participation in S/E Postsecondary Education

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

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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

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Sex-specific probabilities for selected pathways
to an S/E baccalaureate
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Sex-specific probabilities for selected pathways
to an S/E baccalaureate
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Participation in S/E Postsecondary Education

• After the transition to college, there are no
  gender differences in persistence

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

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Post-S/E baccalaureate career paths
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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

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Post-S/E baccalaureate career paths
Female-to-Male Odds Ratios of Career Transitions

Bachelors

Degree in S/E

2.44
Graduate
Work

Studies

Graduate
No Graduate
Working in

Graduate
Working in

School in
School, Not
Non
-
S/E

School in S/E

S/E

Non
-
S/E
Working







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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

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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

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Achievement in the S/E labor force

• Women earn significantly less than men

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Achievement in the S/E labor force

• Women earn significantly less than men
• Women are promoted at a significantly lower rate

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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
• Womens family roles hamper their career progress

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Are Womens 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.

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Predicted Migration Rate by Gender and Family
Structure
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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.

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The Productivity Puzzle

• Sex differences in research productivity declined
  between 1960s and 1990s.

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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.

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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
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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

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Does a Family Life Hamper Women Scientists
Careers?
Post-S/E baccalaureate career paths
Bachelor's
Degree in S/E
Graduate Studies
Working
No Grad,
Grad in
Working in
Grad in S/E
Working in S/E
Not Working
Non-S/E
Non-S/E
(State 1)
(State 3)
(State 5)
(State 2)
(State 4)
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Female-to-male odds ratio of post-baccalaureate
career paths by family status
Does a Family Life Hamper Women Scientists
Careers?
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 0.11 0.39
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Female-to-Male Ratio in Labor Force Outcomes by
Family Status
Does a Family Life Hamper Women Scientists
Careers?
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
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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

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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

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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

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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