Does Science Promote Women? Evidence from Academia: 1973-2001

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Does Science Promote Women? Evidence from
Academia 1973-2001

• for presentation at
• Science and Engineering Workforce Project at NBER
• October 20, 2005
• Donna K. Ginther
• University of Kansas
• Shulamit Kahn
• Boston University

2
Introduction

• Federal agencies and others monitor the status of
  women in science and find they are
  under-represented without evaluating likely
  causes.
• CAWMSET (2000)
• GAO (2004)
• Nelson and Rogers (2005)

3
Introduction

• January 16, 2004 Chronicle of Higher Education
  reports Women are Underrepresented in Sciences
  at Top Research Universities
• Is under-representation caused by the promotion
  process?

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Research Question

• Does Science Promote Women?
• We examine gender differences in
• Tenure Track jobs
• Promotion to Tenure
• Promotion to Tenured, Full Professor
• We find negligible gender differences in
  promotion.

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Literature Review

• From Scarcity to Visibility, Long et. al. (2001)
• Shows that women in science, broadly defined,
  have made progress
• Representation, Salary, Promotion
• Aggregates data such that its difficult to
  observe problems

6
Literature Review

• Women in Science, Xie and Shauman (2003)
• Life course approach to science careers
• Sex differences in research productivity have
  declined, explained by observable characteristics
• Find small pay differences, some promotion
  differences for nonacademics

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Literature Review

• Promotion in Science
• NSF (2004)
• Finds significant gender gap in promotion in
  science
• Gap is reduced after controlling for family
  characteristics
• Combine science and social science in the
  analysis

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Literature Review

• Academic Labor Markets
• Promotion differentials Long, Allison and
  McGinnis (1993) Kahn (1993, 1995) Ginther and
  Kahn (2004)
• Ginther and Hayes 1999, 2003 Ginther 2004,
  2003, 2001
• There is no, single academic labor market.

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Data

• Use 1973 - 2001 Survey of Doctorate Recipients
  (SDR)
• Biennial, Longitudinal Survey of U.S. Doctorates
• Used by NSF to analyze scientific labor force

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Data

• Longitudinal Sample Individuals who received
  their Ph.D. between 1972 and 1991 observed
  between 1973 and 2001.
• Tenure-track sub-sample Those who report ever
  having a tenure-track job.

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Data

• Academics in the Sciences
• Life Sciences
• Agriculture and Food Science
• Biology and Life Sciences
• Physical Sciences
• Chemistry
• Earth Science
• Physics
• Computer Science / Mathematics
• Engineering

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Data

• Dependent variables
• Probability of Tenure Track job
• Probability of Promotion to tenure and full
  professor
• Duration between Ph.D. and promotion to tenure
  and full professor

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Data

• Independent variables
• Gender
• Age Ph.D.
• Year Ph.D.
• Race
• Academic field
• Degree institution characteristics

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Data

• Time-varying Independent variables
• University/College employer characteristics
• Rank and Tenure status
• Primary / Secondary work activities
• Government Support of Research
• Publications

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Data Difficulties

• Biennial Survey
• Changes in the sampling frame
• Numerous missing observations, required a lot of
  imputation
• Imputed productivity from three years of observed
  publications

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Empirical Methods

• Probit models (dependent variable)
• Tenure track within 5 years of Ph.D.
• Tenured at 11 years after Ph.D.
• Tenured, Full Professor at 15 years after Ph.D.

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Empirical Methods

• Hazard of Promotion
• Proportional Hazards Model with time-varying
  covariates
• Hazard model is preferred specification

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Stylized Facts

• Womens representation in science depends upon
  the field
• Life ScienceProgress
• Physical Science, Engineering,Anemic
  representation

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Probability of Tenure Track Job
Model 1 Model 2 Model 3 Model 4
Science -0.038 -0.044 -0.031 -0.033
(0.009) (0.009) (0.010) (0.010)
Life Science -0.041 -0.059 -0.075 -0.077
(0.012) (0.013) (0.013) (0.013)
Physical Science -0.002 0.003 -0.010 -0.015
(0.016) (0.016) (0.017) (0.017)
Engineering 0.000 0.014 0.009 0.013
(0.033) (0.034) (0.035) (0.035)
Demographics No Yes Yes Yes
Degree Characteristics No No No Yes
Fields No No Yes Yes
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Probability of Tenure Track JobIncluding family
variables
Science Life Phys. Eng.
Female 0.156 0.108 0.206 0.072
(0.018) (0.025) (0.029) (0.064)
FemaleMarried -0.171 -0.149 -0.236 0.009
(0.024) (0.033) (0.041) (0.092)
FemaleTotal Children -0.029 -0.022 -0.055 -0.053
(0.013) (0.017) (0.022) (0.045)
FemaleYoung Children -0.059 -0.068 -0.021 0.000
(0.028) (0.038) (0.050) (0.100)
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Gender Promotion Gap

• Previous Research (Ginther and Kahn 2004
  Ginther and Hayes 1999, 2003) has shown a
  significant gender promotion gap in
• Economics
• Humanities
• What about science?

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Promotion to Tenure
Full Sample Life Science Physical Science Engineer Ing
Female Probit Coefficient 0.00 -0.03 0.01 0.02
Promoted 11 Yrs Ph.D. (0.88) (0.19) (0.73) (0.75)
Survival Curve 1.26 0.35 0.00 0.49
Homogeneity (0.26) (0.55) (0.95) (0.49)
Female Risk Ratio 0.97 1.02 1.00 1.06
(No Covariates) (0.33) (0.60) (0.96) (0.56)
Model 1 Female Risk Ratio 0.95 0.89 0.93 1.00
(Covariates ex. Productivity) (0.14) (0.02) (0.22) (0.97)
Model 2 Female Risk Ratio 0.97 0.92 0.94 1.03
(Including Productivity) (0.29) (0.07) (0.28) (0.82)
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Promotion to Full Professor
Full Sample Life Science Physical Science Engineer- ing
Female Probit Coefficient -0.05 -0.09 -0.02 0.09
Promoted 15 Yrs Past Ph.D. (0.02) (0.00) (0.51) (0.37)
Survival Curve 7.57 0.61 11.59 0.14
Homogeneity (0.01) (0.44) (0.00) (0.71)
Female Risk Ratio 0.90 0.96 0.79 0.95
(No Covariates) (0.01) (0.48) (0.00) (0.74)
Model 1 Female Risk Ratio 0.95 0.93 0.87 1.09
(Covariates ex. Productivity) (0.34) (0.37) (0.11) (0.89)
Model 2 Female Risk Ratio 0.97 0.96 0.89 1.04
(Including Productivity Covariates) (0.54) (0.61) (0.19) (0.82)
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Tenure at Research I
Full Sample Life Science Physical Science Engineer Ing
Female Probit Coefficient 0.01 -0.03 -0.01 0.00
Promoted 15 Yrs Past Ph.D. (0.84) (0.40) (0.88) (0.97)
Survival Curve 3.48 1.11 0.27 2.97
Homogeneity (0.06) (0.29) (0.61) (0.08)
Female Risk Ratio 0.92 0.94 0.96 1.24
(No Covariates) (0.10) (0.35) (0.65) (0.14)
Model 1 Female Risk Ratio 1.00 0.91 0.97 1.17
(Covariates ex. Productivity) (0.99) (0.22) (0.72) (0.33)
Model 2 Female Risk Ratio 1.02 0.93 0.98 1.23
(Including Productivity Covariates) (0.75) (0.31) (0.86) (0.20)
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Full Professor at Research I
Full Sample Life Science Physical Science Engineer-ing
Female Probit Coefficient -0.04 -0.06 -0.04 0.27
Promoted 15 Yrs Past Ph.D. (0.24) (0.11) (0.56) (0.09)
Survival Curve 15.69 6.79 9.52 0.00
Homogeneity (0.00) (0.01) (0.00) (0.95)
Female Risk Ratio 0.77 0.80 0.68 0.99
(No Covariates) (0.00) (0.02) (0.01) (0.95)
Model 1 Female Risk Ratio 0.89 1.02 0.68 1.02
(Covariates ex. Productivity) (0.18) (0.87) (0.01) (0.95)
Model 2 Female Risk Ratio 0.91 1.01 0.71 1.07
(Including Productivity Covariates) (0.23) (0.90) (0.03) (0.78)
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Conclusions

• Does Science Promote Women?
• YES
• Gender differences in tenure track
• Explained by marriage and family.
• Little evidence of gender promotion gap to
  tenure, full professor.

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Conclusions

• One exception
• Full Professors in Physical Science at Research I
  Universities
• Each academic field presents different hurdles
  for women in terms of pay and promotion.
• Science 12 gender gap in salaries at Full
  Professor (Ginther 2004)