RESEARCH ARTICLE - IA de Investigación especializada en el MIT

ARTÍCULO DE INVESTIGACIÓN

The institutionalized stratification of the
Chinese higher education system

Fei Shu1

, Cassidy R. Sugimoto2

, and Vincent Larivière3

1Chinese Academy of Science and Education Evaluation (CASEE), Hangzhou Dianzi University,
Xiasha, Hangzhou, Zhejiang (China P.R.)
2School of Informatics, Computing and Engineering, Universidad de Indiana, Luddy Hall,
700 norte. Woodlawn Avenue, Bloomington, Indiana (EE.UU)
3École de bibliothéconomie et des sciences de l’information, Université de Montréal,
C.P. 6128, Succ. Centre-Ville, Montréal, QC. H3C3J7, Canada

Palabras clave: Double First Class, elite university, higher education, nonelite university, Proyecto 211,
Proyecto 985

ABSTRACTO
To promote research excellence, China’s government has been offering substantial financial
support for a small group of selected universities through three national research programs
(Proyecto 211, Proyecto 985, Double First Class). Sin embargo, admission to these programs may not be
completely merit based. Based on a statistical analysis of Chinese universities’ scientific activities,
this paper shows that this institutionalized hierarchy is not supported by empirical data on research
actuación, which contributes to inequalities and inefficiencies in Chinese higher education. A
build and maintain research capacity, China must support meritocracy across the research system.

INTRODUCCIÓN

1.
China’s research activities experienced rapid growth over the last 25 años, in parallel with the
significant development of its economy. En 2017, China surpassed the United States to become
the largest producer of scholarly papers (Junta Nacional de Ciencias, 2018). In addition to sizable
investments—China is now the world’s second largest R&D spender (Normile, 2018)—this
growth in scholarly production can be associated with the creation, since the 1990s, of three
national programs promoting university research (Proyecto 211, Proyecto 985, and Double First
Clase). These programs provide substantial financial support to a small group of selected univer-
sities that now represent the bulk of the research output of the country (57.5% of China’s Web
de Ciencia [ WoS] publicaciones [National Bureau of Statistics of China, 2019]). Sin embargo, estos
programs have also been criticized for lacking transparency in how universities are chosen for
admission, as well as perpetuating inequalities in the Chinese higher education system (chi, 2017).
This paper describes the development and stratification of China’s higher education system, con
an analysis of universities’ scientific output since the 1990s.

2. THE CHINESE HIGHER EDUCATION SYSTEM

Research in China is performed in an array of organizational settings: higher education institutions,
scientific institutes, hospitals, and industry. As is common across most countries (Larivière, Macaluso
et al., 2018), higher education contributes the largest share of China’s basic research production,
representing 83.5% of monographs and 75.5% of journal articles (National Bureau of Statistics of
Porcelana, 2019) incluido 85.1% of WoS publications. Scientific institutes (p.ej., Academia China de

un acceso abierto

diario

Citación: Shu, F., Sugimoto, C. r., &
Larivière, V. (2020). The institutionalized
stratification of the Chinese higher
education system. Quantitative Science
Estudios, 2(1), 327–334. https://doi.org
/10.1162/qss_a_00104

DOI:
https://doi.org/10.1162/qss_a_00104

Recibió: 6 Puede 2020
Aceptado: 11 Agosto 2020

Autor correspondiente:
Fei Shu
fei.shu@hdu.edu.cn

Editor de manejo:
Lin Zhang

Derechos de autor: © 2020 Fei Shu, Cassidy R.
Sugimoto, and Vincent Larivière.
Publicado bajo Creative Commons
Atribución 4.0 Internacional (CC POR 4.0)
licencia.

La prensa del MIT

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The institutionalized stratification of the Chinese higher education system

Ciencia) contribute 9.4% of WoS publications (ISTIC, 2019) in China. There are many higher
educational institutions producing this work: China boasts 2,688 higher education institutions,
incluido 1,423 universities offering 4-year undergraduate programs and 1,388 colleges offering
3-year college diploma programs (Ministry of Education of China, 2019). Not all institutions,
sin embargo, are given the same amount of resources.

Institutionalized stratification of Chinese higher education started in 1954, when six Chinese uni-
versities were designated by the Communist Party as the first group of elite universities (“重点大学”
in Chinese). This group of elite universities increased to 16 en 1959, 64 in the 1960s, 88 in the 1970s,
y para 99 in the 1980s. One common characteristic of elite universities is that they are generally
administered by the Ministry of Education (MoE) or by the central government, while nonelite uni-
versities are managed by provincial or local governments. Elite universities have priority over non-
elite universities to admit students, while nonelite universities can only admit the remaining
estudiantes; they also benefit from preferential financial policies (Hu, 2011). Stratification of
Chinese higher education crystallized in 1995 with the creation of Project 211 by the MoE, con
the objective of creating 100 world-class universities by the beginning of the 21st century (Ministerio
of Education of China, 2000). The Chinese government offered preferential policies (como el
priority to admit the best students) and financial support to universities who were part of the group.
Between 1995 y 2008, el 112 universities admitted to Project 211 received 70% of national
research funding and 80% of doctoral students (Espiga & Cual, 2008).

En 1998, Jiang Zemin, then Chairman of the People’s Republic of China, created Project 985 a
promote the development of a Chinese equivalent to the U.S. Ivy League (Jiang, 1998). The pro-
gram started with nine universities in 2009 and added another 30 universities in the 2 following
años. Estos 39 universities are all part of Project 211, but are provided with additional resources.
In addition to Project 211 universidades, a subset of universities owned by provincial governments
signed cooperation agreements and received support from both their province and ministries of
the central government; these are also recognized as elite universities. Prior to the launch of the
Double First Class program in 2017, Había 141 elite universities (as shown in Figure 1) defined

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Cifra 1. Hierarchy of China’s higher education institutions.

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328

The institutionalized stratification of the Chinese higher education system

by the MOE as “universities admitted to Project 211 or co-operated by ministries and provinces”
(Ministry of Education of China, 1992–2017). These national programs are controlled by the MoE,
and while inclusion is purportedly based on the quality of research, teaching, and reputation, el
detailed methodology has never been revealed. Inclusion in those categories is also driven by geo-
política, as the MoE required that each province had at least one university in Project 211.

The Double First Class program (“双一流” in Chinese) was initiated by the Chinese government
en 2017, aiming to build an excellent higher education system including both “First Class” univer-
sities and “First Class” disciplines, as both Project 985 and Project 211 officially concluded.
Sin embargo, the concepts of Project 985 and Project 211 are still used, not only in academe but also
in industry, which uses graduation from Project 985 and Project 211 universities as a threshold in
hiring (Hartog, Sol, & Ding, 2010; Mok & Jiang, 2017). As the “Double First Class” program is
recent and our data ends in 2017, we do not focus on this new program but, bastante, on those that
existed prior to 2017.

3. THE BENEFITS OF THE ELITE

One of the strongest benefits of being classed as an elite institution is the influx of funds provided by
el gobierno. Como figura 2 muestra, en 1991, research funding1 per capita was, on average, $2,944 for elite universities and $1,026 for nonelite universities, with nonelite universities obtaining about
35% of the funding obtained by elite ones. Despite an increase in research funding over years, este
ratio remained unchanged in 2016, with research funding per capita at $160,745 for elite univer- sities and $57,296 for nonelite universities (Ministry of Education of China, 1992–2017).

Admission to the elite brings immediate benefits to the university. Por ejemplo, en 2008, el
last five universities were admitted to Project 211. As Table 1 muestra, all five new elite universities
experienced a radical increase in terms of research funding received after their admission to
Proyecto 211, que van desde 74.65% a 600.24%, which are much higher than the average increase
rates of all elite universities (69.59%) and all nonelite universities (54.21%) in the same period.

Such advantages are also observed in terms of external research funding from research coun-
cils. According to the Natural Science Foundation of China (NSFC) (2008–2017), the average
acceptance rates of applications from elite universities ranged from 20.3–30.6%, while the aver-
age acceptance rates of nonelite university range from 12.5–17.5%. This gap in acceptance rates
has widened over time, de 59% en 2008 (20.3% vs. 12.8%) a 82% en 2017 (27.9% vs. 15.3%).
Sin embargo, the higher acceptance rate of applicants from elite universities does not convert into
higher completion rate. In China, all NSFC-funded projects are evaluated after the funded period,
and those that do not meet their objectives are graded as incomplete. While most projects are
considered as complete, 13.6% of research projects (27,041 de 171,372) funded by the NSFC
entre 2003 y 2012 were considered as incomplete. The results show that researchers from
nonelite universities are more likely to complete the projects for which they were funded: Mientras
solo 8.3% of projects from nonelite universities remained incomplete, this percentage was 14.0%
for elite universities (NSFC, 2008–2017).

Elite universities also have advantages in terms of administration and international visibility:
They have independence over the promotion of their professors, while promotion at nonelite uni-
versities is made by the MoE. This leads to a gap in the proportion of tenured professors (es decir.,

1 “Research funding” is defined by the MOE as all investments received for research, which includes the fund-
ing from universities’ own budgets, funding agencies as well as special contributions from the government
and industry.

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The institutionalized stratification of the Chinese higher education system

Cifra 2. Research funding per capita in China’s universities (1991–2016).

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associate and full professors): En 1991, the proportion of tenured professors in elite universities
era 50% higher than in nonelite universities (39.2% vs. 26.1%). This gap decreased to 42% en
2016 (63.0% vs. 44.5%). Professors from elite universities are also more likely to attend interna-
tional conferences, as they are provided with adequate funding to cover travel costs. Mientras
77.1% of professors from elite universities attended at least one international conference in
2016, this percentage was only 16.1% for nonelite universities. Similarmente, 15.4% of elite univer-
sity professors have visited a foreign institution as a visiting scholar, while only 5.9% of nonelite
university scholars had the same experience (Ministry of Education of China, 1992–2017).

4. THE PERFORMANCE OF THE ELITE

The benefits provided to elite universities, sin embargo, do not translate into greater scientific pro-
duction and impact. While elite universities received, on average, 2.3 times more funding per
capita than their nonelite counterparts ($722,128 vs. $312,277 over the 2007–2016 period), su

Mesa 1.

“Welcome bonus” for entering the “elite club”

Universidad
Tibet University

Hainan University

Ningxia University

Shihezhi University

Qinghai University

All elite universities

All nonelite universities

2005–2007

5.13

8.050

5.47

14.53

16.24

14617.06

6379.43

Fuente: Ministry of Education of China (1992–2017).

Research funding ($millón) 2008–2010 35.89 Cambiar (%) 600.24 22.29 15.04 28.69 28.36 24788.98 9837.91 176.87 174.75 94.53 74.65 69.59 54.21 330 Quantitative Science Studies The institutionalized stratification of the Chinese higher education system l D o w n o a d e d f r o m h t t p : / / directo . mi t . / e d u q s s / a r t i c e – pdlf / / / / 2 1 3 2 7 1 9 0 6 6 6 9 q s s _ a _ 0 0 1 0 4 pd . / f por invitado 0 7 septiembre 2 0 2 3 Cifra 3. Cost per paper among Chinese universities (2007–2016). number of papers per capita was only 19.4% higher than nonelite counterparts (40.777 vs. 34.153) and researchers from nonelite universities published, on average, a higher mean number of monographs per capita (0.583 vs. 0.364). This is also observed at the level of specific univer- ciudades. Cifra 3 presents, for both elite and nonelite universities, the monetary cost (research fund- ing per paper) and the human capital cost (full-time equivalent per paper) of a single paper. Elite universities (nodos rojos) need much more funding to produce a single paper comparing with non- elite universities (nodos azules). A further investigation was conducted regarding the research input and output of the subset of Chinese universities that published at least 2,000 research articles and at least 700 interno- tional papers indexed by WoS between 2007 y 2016 (norte = 198 universidades). This subgroup of very productive institutions contains as many elite universities (97 universidades) as nonelite ones (101 universidades). As shown in Table 2, while these 97 elite universities received, on average, 1.9 times more funding per capita than their 101 nonelite counterparts ($942,463
vs. $506,754 over the 2007–2016 period), their research outcomes per $1 million spending
remain lower than nonelite counterparts. More specifically, elite universities publish fewer in-
ternational papers indexed by WoS (9.671 vs. 13.283), a lower number of local Chinese

Mesa 2. Comparison between elite universities and nonelite universities in terms of research outcome per $1 million spending (2007–2016) Group Elite (norte = 97) Mean funding per capita $942,463

Mean number
of international
documentos ( WoS)
9.671

Mean number
of international
citas ( WoS)
96.601

Mean number of
papers in national
(Chino) journals
35.785

Mean number
of monographs
0.198

Nonelite (norte = 101)

$506,754

13.283

96.797

82.057

0.388

Fuente: Ministry of Education of China (1992–2017).

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The institutionalized stratification of the Chinese higher education system

documentos (35.785 vs. 82.057), fewer monographs (0.198 vs. 0.388) (Ministry of Education of
Porcelana, 1992–2017; Qiu, Tang et al., 2008–2017), and receive nearly identical citations per
paper (96.601 vs. 96.797) (using citation data from WoS).

5. TOWARDS A ROBUST AND EQUITABLE HIGHER EDUCATION SYSTEM

Since the 1950s, the Chinese government has maintained a clear stratification in the higher ed-
ucation system, in which most of the resources are concentrated in the hands of a small number of
universidades. This stratification has put elite universities in a privileged position, in which they
obtain the majority of government resources and their faculty have both better career advance-
ment opportunities and greater access to the international community. Given this access to resources
and preferential policies, elite universities are more likely to attract and retain elite scholars and,
por lo tanto, to preserve and accelerate advantages, leading to an institutionalized Matthew Effect
(Merton, 1968).

While previous studies attribute this Matthew Effect to the uneven distribution of scientific
resources (Cual, Gu et al., 2015) or the bureaucratic administration in science (Shi & Rao, 2010),
we argue that such cumulative advantages are rooted in the hierarchal structure of China’s higher
education system and its relationships with the political organization of the country. Por ejemplo,
university administrative ranks correspond to that of the government and, por lo tanto, each adminis-
trative staff level, from department chair to university president, has its counterpart in the govern-
mento. Por lo tanto, the categorization of the universities has a strong effect on the political ties that
university administrations can have. Por ejemplo, the president of Peking University (an elite
vice-ministerial rank university) is the counterpart of the vice-minister of the MoE, while the presi-
dent of Guangzhou University (a nonelite department rank university) is the counterpart of the
director of Guangdong Provincial Department of Education. Considering the hierarchical gov-
ernment administration in China (cheng, 2017), universities with higher rank are more powerful
than their lower ranked counterparts when negotiating with the government for extra funding
and preferential policies, and lobbying science policies regarding national research projects.

Además, as elite universities are generally administered by the central government (mientras
nonelite universities are managed by local governments), the administrative ranks of their staff
are generally higher than their nonelite counterparts, which leads to a natural stratification in
China’s higher education system. Elite universities also have the advantage in their guanxi (one’s
close personal relationships) (Shi & Rao, 2010), having closer contacts with senior government
officials who design and implement science polices. En efecto, elite universities benefit from their
strong alumni network, as all 709 senior officials with ministerial rank and above in Chinese
government are alumni of elite universities (Xinhua News, 2017). With this strong alumni net-
trabajar, elite universities can lobby the MoE or other ministries for preferential policies, helping
them keep their elite statuses at the expense of nonelite universities. This is why these national
research programs were criticized for lacking transparency and inequalities (chi, 2017) as they are
tailormade for elite universities.

Despite these advantages, elite universities strongly underperform relative to other high pro-
ducing Chinese institutions. They publish on average, fewer articles—in both national and inter-
national venues—and fewer monographs. This suggests that the stratification of elite institutions is
not meritocratic, but highly dependent on factors such as guanxi, bureaucratic power (Shi & Rao,
2010), geopolitics, and administrative ranks. The classification, por lo tanto, lacks distinction. If any-
thing, the elite classification is aspirational, rather than descriptive.

A new list of 42 “First Class” universities and 95 universities having “First Class” disciplines
were announced by the Double First Class program in 2017, forming a new group of 137 elite

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The institutionalized stratification of the Chinese higher education system

universidades. Todo 39 universities included in Project 985 were admitted to the “First Class” univer-
sities and all Project 211 universities had “First Class” disciplines. It seems that the same story in
the admission of Project 985 and Project 211 happened again; universities are admitted not on
their research performance, but on their past classification. Although the detailed methodology
has not been revealed, some clues showed that some elite universities were allowed to designate
one discipline as the “First Class” discipline while other “First Class” disciplines were appraised
by the Double First Class Selection Committee, which confirms the privilege of elite universities
in China’s higher education system again.

En resumen, institutionalized stratification exists in the Chinese higher education system on
which China’s national research programs are based. If China hopes for these classifications to
be meaningful, the admittance to the elite club should be both transparent and evidence based.
Without this rigor, the artificial classification of research institutions in China is likely to continue to
lead to inefficiencies and suppress innovation in the Chinese higher education system.
Además, although China used to have scarce resources devoted to science and therefore
had to be selective in funding (Jiang, 2000), the government now invests more than 2% of GDP
(Banco mundial, 2018). These resources should be spread meritocratically, so that China can realize
its full scientific potential.

CONTRIBUCIONES DE AUTOR
Fei Shu: Conceptualización; Análisis formal; Investigación; Metodología; Validación; Writing—
original draft; Cassidy Sugimoto: Escritura: revisión & edición. Vincent Larivière: Escritura: revisión
& edición

CONFLICTO DE INTERESES

Los autores no tienen intereses en competencia.

INFORMACIÓN DE FINANCIACIÓN

We gratefully acknowledge support from the Social Science and Humanities Research Council
Canada (SSHRC) under grant number 756-2019-0196.

DISPONIBILIDAD DE DATOS
Data used in this manuscript are partly subject to the Law of the People’s Republic of China on
Guarding State Secrets and cannot be made available in a data repository.

REFERENCIAS

cheng, q. (2017). Xing zheng ji bie de ji li luo ji rong na xian
zhi ji qi tan xing tuo zhan (The logic, incentive, capacity, flex-
ibility of Administrative Rank). Jiangsu Social Sciences, 2017(5),
116–123.

Hartog, J., Sol, y., & Ding, X. (2010). University rank and bachelor’s
labour market positions in China. Revisión de la economía de la educación,
29(6), 971–979. DOI: https://doi.org/10.1016/j.econedurev
.2010.06.003

Hu, B. (2011). The history of the elite university system (in Chinese).
Higher Education Development and Evaluation, 27(5), 9–12.
ISTIC. (2019). Statistical data of Chinese S&T papers 2019. Beijing:

ISTIC.

Jiang, z. (1998). Speech at the celebration of the Centennial of
Peking University. China University Teaching, 1998(4), 3–5.
Jiang, z. (2000). Science in China. Ciencia, 288(5475), 2317. DOI:

https://doi.org/10.1126/science.288.5475.2317

Larivière, v., Macaluso, B., Mongeon, PAG., Siler, K., & Sugimoto, C. R.
(2018). Vanishing industries and the rising monopoly of universi-
ties in published research. MÁS UNO, 13(8), e0202120. DOI:
https://doi.org/10.1371/journal.pone.0202120, PMID: 30107002,
PMCID: PMC6091964

Merton, R. k. (1968). The Matthew Effect in science. Ciencia, 159(3810),
56–63. DOI: https://doi.org/10.1126/science.159.3810.56, PMID:
5634379

Ministry of Education of China. (1992–2017). Scientific statistics in
higher education institutions. Beijing: Higher Education Press.
Ministry of Education of China. (2000). Introduction to the Project
211. Retrieved from http://www.moe.edu.cn/publicfiles/business
/htmlfiles/moe/moe_846/200804/33122.html.

Ministry of Education of China. (2019). List of higher education in-
stitutions. Retrieved from http://www.moe.gov.cn/jyb_xxgk
/s5743/s5744/201906/t20190617_386200.html.

Estudios de ciencias cuantitativas

333

D
oh
w
norte
oh
a
d
mi
d

F
r
oh
metro
h

t
t

pag

:
/
/

d
i
r
mi
C
t
.

metro

i
t
.

mi
d
tu
q
s
s
/
a
r
t
i
C
mi
–
pag
d

F
/

2
1
3
2
7
1
9
0
6
6
6
9
q
s
s
_
a
_
0
0
1
0
4
pag
d

b
y
gramo
tu
mi
s
t

oh
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0
7
S
mi
pag
mi
metro
b
mi
r
2
0
2
3

The institutionalized stratification of the Chinese higher education system

Mok, k. h., & Jiang, j. (2017). Massification of higher education:
Challenges for admissions and graduate employment in China. En
k. h. Mok (Ed.), Managing international connectivity, diversity of
learning and changing labour markets (páginas. 219–243). Singapur:
Saltador. DOI: https://doi.org/10.1007/978-981-10-1736-0_13
National Bureau of Statistics of China. (2019). China statistical year-

libro. Beijing: China Statistics Press.

Junta Nacional de Ciencias. (2018). Science and Engineering Indicators
2018 (NSB-2018-1). Alejandría, Virginia: Fundación Nacional de Ciencia.
Retrieved from https://www.nsf.gov/statistics/indicators/.

Normile, D. (2018). China narrows U.S. lead in R&D spending.
Ciencia, 362(6412), 276. DOI: https://doi.org/10.1126/science
.362.6412.276, PMID: 30337391

NSFC. (2008–2017). National Natural Science Foundation of China

Estadísticas. Beijing: NSFC.

chi, W.. (2017). Comentario: Programmed to fulfill global ambitions.
Naturaleza, 545, S53. DOI: https://doi.org/10.1038/545S53a, PMID:
28538712

Qiu, j. PAG., Espiga, j. METRO., zhao, R. y., & Wang, B. Y. (2008–2017).
Chinese university and discipline evaluation report. Beijing:
Science Press.

Shi, y., & Rao, Y. (2010). China’s research culture. Ciencia, 329
(5996), 1128. DOI: https://doi.org/10.1126/science.1196916,
PMID: 20813923

Espiga, J., & Cual, C. (2008). Encima 10 billion yuan to be invested in

“211 Project”. Beijing: Xinhua News.

Banco mundial. (2018). World development indicators: Science and
tecnología. Retrieved from http://wdi.worldbank.org/table/5.13.
Xinhua News. (2017). Resumé of the members of the 19th Central
Leading Body of the Communist Party of China. Retrieved from
http://www.gov.cn/zhuanti/2017-10/25/content_5234457
.htm#1

Cual, X., Gu, X., Wang, y., Hu, GRAMO., & Espiga, l. (2015). The Matthew
Effect in China’s science: Evidence from academicians of Chinese
Academia de Ciencias. cienciometria, 102(3), 2089–2105. DOI:
https://doi.org/10.1007/s11192-014-1502-5

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