gender & equity in china’s education system

8/2/2019 Gender & Equity in Chinas Education System

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Gender & Equity

in Chinas Education System

Prashant Loyalka

May Maani

China Institute for Educational Finance Research (CIEFR)

Peking University

2012.2.27

The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of the AsianDevelopment Bank (ADB), or its Board of Governors, or the governments they represent. ADB does not guarantee the accuracy ofthe data included in this paper and accepts no responsibility for any consequence of their use. The countries listed in this paper donot imply any view on ADB's part as to sovereignty or independent status or necessarily conform to ADB's terminology.


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Outline

Brief background & literature review

National trends in gender & education

Variation across provinces

Gender sorting along the education/STEMpipeline: case study from northwest China


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Background

Traditional vs. Marxist Values: Traditional: woman as wife and mother; marry out

Marxist: women and men have equal rights

Legislative equality (1949): Women hold up half the sky

Economic Reform Policies (late 1970s):

More opportunities for social and economic development

Females more vulnerable to labor market discrimination, as

gradually no state job assignments


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One Child Policy & Demographic Changes

One Child Policy (1979) increased prenatal sex selection(Ebenstein, 2008)

Tighter fertility control = higher sex ratio (biased against girls)

Sex ratio: Highest for 1st births & 2nd births following daughters

2005: # boy births = # girl births + 1.1 million (Zhu, 2008)

In 2012, male-female ratio at birth was 1.13: 1 (vs. 1.06:1)

Keep in mind when examining female student enrollment data


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Literature: gender & educational attainment

Interest in the topic in the 1990s & early 2000s

1990s: Rural girls had low enrollment & graduation rates(Connelly & Zheng, 2002; Hannum, 2003)

Enrollment gaps closed: esp. in HE by 2005

Slight gap: transition from high school to HE (Wu & Zhang, 2010)


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Studies on gender and educational achievement

One District in Beijing (1999-2002):

Girls scores higher in grades 1-9

Boys catch up (Lai, 2009)

Rural Gansu: Gender gaps?

Parents invest similarly

School grades similar

Some traditional attitudes:

Chores

ROR to males vs. females

(Hannum et al., 2009)


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Studies on gender and educational achievement:

Shanghai PISA 2009


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National Trends

&

Provincial Variation


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Primary School & Junior Secondary School

(% of females)

0

10

20

30

40

50

2000 2005 2010

Primary School

Age cohort

Schools

0

10

20

30

40

50

2003 2005 2010

Junior Secondary School

Proportion of females in school greater than proportion of females in age group:

Male repeaters > female repeaters: 42% of repeaters in primary school

39% of repeaters in junior secondary school

Female students are less likely to drop out of school (Loyalka et al., 2012)


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Senior Secondary School (%):

- Vocational and Regular -

05

1015

20253035404550

2003 2006 2010

Regular

Increasing female proportions in senior secondary school:

More males discontinue schooling past junior secondary level

Relatively higher ROR for males attending vocational school or in labor force

Higher proportion of males in Skilled Worker Schools (SWS)

05

1015

20253035404550

2000 2006 2010

Vocational

Schools

SWS

Age cohort


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Higher Education Institutes (%):

- Vocational and Regular -

05

101520

25303540455055

2004 2007 2010

Vocational College

Schools

05

101520

253035404550

2004 2007 2010

Regular College

Females more likely than males to attend tertiary education

Females in vocational colleges: above 50% -- possibly because

fewer females go to expensive private 4-yr HEIs (Loyalka, 2009).

Age cohort


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Kindergarten/Pre-School

05

1015

20253035404550

2000 2003 2005 2007 2010

% of Females in School

Schools

Age cohort*


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% of Females in Graduate Programs

0

10

20

30

40

50

60

70

U.S. 2000 U.S. 2010 China 2004 China 2010

Masters

PhDs


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Variation across Provinces:% Female in Grades 1-12 (academic track)

05

10

15

20

25

30

35

40

45

50

0 10000 20000 30000 40000 50000

Per Capita Gross Regional Product (Yuan)

Primary School (%)

Middle School (%)


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Variation across Provinces:

% Female in Higher Education

05

10

15

20

25

30

35

40

45

50

55

0 10000 20000 30000 40000 50000 60000 70000

Per Capita Gross Regional Product (Yuan)

HEIs (%)


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What the Big Picture Tells Us

National trends about gender & education are positive:

Female enrollment ratios are high

Female achievement levels are high:

Girls in Beijing score better up till age 15. Same in Shanghai.

Girls in rural Gansu perform similarly to males

Unexplored area: gender & STEM education after JHS

Why do we care?

China produces ~11 times more BA engineering graduatesas the US each year (Carnoy et al., 2012).

Thus gender disparities in STEM in China would affectinternational community of scientists and engineers.


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Gender & STEM Education in China


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Issue: The Post-JHS

Education Pipeline

Student choices/tracking

after JHS

Choices unidirectional &

irreversible

Females sorted into &

away from STEM along

this pipeline

High School Entrance Exam

(HSEE/Zhongkao)

Different Levels of Academic High School

(Key, County-Level, Township-Level)

Different Levels of Vocational

High School

Grades 1-3 tracking:

Fast / Regular

Grade 2 Choice:

Science track Humanities track

College Entrance ExamScience Exam Humanities Exam

College Choice Form

Admissions Process

Vocational College

Entrance Exam

1st, 2nd,and 3rd Tier Colleges

(4-year degrees)

4th Tier Colleges

(3-year degrees)

Repeat College

Entrance Exam


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Case Study: One NW Region in China

Use administrative student-level data

Track students from high school entrance exam

(HSEE) to college admissions

Basic background info, scores, college-majors

Entire region

(developed City Y vs. less developed Cities G&W)

From 2001 to 2010 (over course of HE expansion)


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At the Start of the Pipeline:HSEE scores in City Y


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At the Start of the Pipeline:HSEE scores in Cities G & W


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Key High School Attendance

Non-Poor Poor

Total Population 48% 49%

High School Attendees 51% 47%

Key High School Attendees 51% 47%

2010


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Proportion of Females in each CEE Track

0%

10%

20%

30%

40%

50%

60%

70%

80%

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Humanities

Science

So as the % of females in HE has increased over time,

more have gone into the humanities vs. science track.


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Quantile regression ofScience-Track CEE score onfemale (above) and other background covariates.

-.1

0

.1

.2

.3

.4

0 .2 .4 .6 .8 1Quantile

Quantile slope coefficient Upper 95% bs confidence band

Lower 95% bs confidence band

Coefficient of female

Slope Estimates (Science Track Gaokao as DV)


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% of Females in Elite HEIs vs. other Bachelors programs (Science Track)

211 Elites

985 Elites

25%

30%

35%

40%

45%

50%

200

1

200

2

200

3

200

4

200

5

200

6

200

7

200

8

200

9

201

0

non-211(Bachelors)

elite 211+985

20%

25%

30%

35%

40%

45%

50%

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

non-985 (Bachelors)

elite 985


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0%

10%

20%

30%

40%

50%

60%

70%

80%

% Females in Selected Engineering Majors (Bachelor's Programs)

2001

2010


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Implications of the Science vs. Humanities Track Choice

What are the causal impacts of choosing thescience vs. the humanities track on studentschances of getting into college & selectivecolleges? IV analyses

Finding:

(1) Choosing the science track increases femalestudents chances of going to 4-yr. HEIs & or any (3or 4-yr.) college by 20-25%.


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Conclusions (1) Female-male birth ratio is lopsided (self-selection)

Female enrollment ratios risen and high in all education

levels (except doctoral education)

Stats on inter-provincial variation sparse, but likely not

much variation now

Females overall achievement is comparable to males, at

least in urban areas, and close in rural areas.


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Conclusions (2) Gender and the STEM education pipeline

1) Females score as well in math/science in urban areas (except at theupper end of the score distribution) and somewhat less well inrural areas

2) A highly disproportionate number of females choose thehumanities over science track

3) Choosing humanities reduces females likelihood of gainingadmission to HE

4) (Self-selected) females do as well as males on the science-trackCEE, except at the upper end

5) Females in the science track are underrepresented in elite colleges,private colleges, and in likely in graduate programs

6) Females are less represented in most engineering majors

High school: a key area to encourage girls to do well in and pursue

STEM in China

gender & equity in china’s education system

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