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Table 1 Descriptive statistics by upper-secondary track

From: Gender gap in STEM pathways: the role of secondary curricula in a highly differentiated school system—the case of Chile

Variables

Entire sample (Mean)

Sub-sample AE

Sub-sample VE

Total (Mean)

STEM (Mean)

Non-STEM (Mean)

Total (Mean)

STEM (Mean)

Non-STEM (Mean)

Students characteristics

 Women = 1; else = 0

0.52

0.55

0.51

0.59

0.49

0.17

0.69

 Socioeconomic status (St)

− 0.38

0.01

0.14

− 0.08

− 0.78

− 0.70

− 0.82

 Ln income per capita (St)

10.99

11.17

11.23

11.13

10.80

10.84

10.77

 Father’s education (St)

− 0.20

0.07

0.16

0.01

− 0.47

− 0.41

− 0.50

 Mother’s education (St)

− 0.19

0.08

0.16

0.01

− 0.46

− 0.41

− 0.50

 Attendance 10th grade (St)

0.10

0.16

0.25

0.10

0.03

0.10

− 0.01

 GPA 10th grade (St)

0.00

0.21

0.44

0.03

− 0.20

− 0.25

− 0.17

 SIMCE language (St)

− 0.08

0.18

0.29

0.10

− 0.34

− 0.35

− 0.34

 SIMCE math (St)

− 0.12

0.16

0.45

− 0.03

− 0.42

− 0.28

− 0.48

 Expected higher education = 1; else = 0

0.91

0.96

0.98

0.95

0.85

0.84

0.86

 Enrollment in Higher Education = 1; else = 1

0.73

0.86

0.90

0.83

0.60

0.59

0.60

 Enrollment in VE-STEM = 1; else = 0

0.14

0.10

0.11

0.10

0.18

0.36

0.07

 Enrollment in university-STEM = 1; else = 0

0.10

0.16

0.25

0.09

0.04

0.07

0.03

School characteristics

 School SES (St)

− 0.32

0.00

0.10

− 0.07

− 0.65

− 0.60

− 0.69

 Rural school = 1; else = 0

0.03

0.02

0.02

0.02

0.05

0.05

0.05

 Public school = 1; else = 0

0.38

0.35

0.25

0.42

0.40

0.39

0.41

 Subsidized private school = 1; else = 0

0.62

0.65

0.75

0.58

0.60

0.61

0.59

Number of observations

125,628

63,561

25,956

37,605

62,067

22,892

39,175

  1. High school graduates sample
  2. VE = vocational education; AE = academic education; ln income per capita = logarithm of the family income per capita; St indicates that the variable was standardized to a mean of 0 and a standard deviation of 1