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Abstract

DOUBLE FIRST-CLASS PROJECT IMPLEMENTATION: THE INFLUENCE OF LOCAL GOVERNMENT IN CHINA

Xin Fangkun

Shanghai University of Political Science and Law

School of Government Management

China, Shanghai

This paper discusses the influence of local governments over the realization of Double First-Class project in China. Based on the qualitative analysis of 36 universities' mid-term reports, the spillover effect on local economic and social development was found to be enhancing the core competitiveness of local governments. Text analysis of eight local governments' Double First-Class implementation reports showed that the way of their promoting the Double First-Class construction were investment and talent introduction. The local participation in the Double First-Class competition under the constraint of national financial resources leads to the Matthew effect of university development. Universities selected for Double First-Class will get more resources and develop better, while other universities will be left behind. Therefore, the central government needs to intervene the competition of local governments.

Keywords: Double First-Class implementation, local government, spillover effect, financial support, policy driven, social services, local development

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Table 1

36 universities - Double First-Class project participants' impact effect in their regions

, .

, %

, , , , , ,

28

77,78

- , - , , , ,

28

77,78

, , , - , , , , ,

25

69,44

, , , , , , , ,

13

36,11

, , , - - ,

12

33,33

, - . 2019 256 ; 34 , ; 26 ; 45 , .

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2


Table 2

Comparative table of local governments' financial investments in the Double First-Class project implementation

/

, 100

3

16,7

-

5

10,0

4

9,0

5

15,0

5

5,0

10

3,1

5

1,0

2017 2020

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3

QS

Table 3

QS World University Rankings

, 2020

, 2019

, 2018

16

17

25

22

30

38

40

44

40

54

68

87

60

59

62

-

89

98

97

120

122

144

257

257

282

265

291

316

277

292

256

277

285

325

287

295

319

. : QS top universities : . URL: https://www.topuniversities.com/university-rankings/rankings-by-location/mainland-china ( : 06.01.2020).

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1. N. oꗬ??[O?ج[,]?. 2016 N. 4. 21-27?.

2. ?. oꗬ?????O?貤, ]?. 2016N. 6. 60-64?

3. 牶,?. ?@ɤ@yj?M@y?? l^??, . 2017N. 3. 18-23?

4. ?. 𒆍??G_J?R. Љ ?s. 2019N. 2. 69-78?

5. H^,??w. ??Oի----n{oꗬ? s????s. ?NШ|??. 2019N. 1. 58-63?

6. ??Dn{?@yj?O@y?? ^v|QSn擑oꗬ{ÍminD . 2017N. W. 50-67?.

7. C?. oꗬ?aF???R. ]? . 2018N. 6. 17-23?

8. ??M. F?isa?. . 2018N. 4. 12-15?

9. ??. Ȉ捂n?U_. 猤. 2017N. 11. 39-45?

10. Heclo H. Review Article: Policy Analysis // British Journal of Political Science. 1972. Nr 2. P. 83-108.

11. Bird R. Reflections on the British Government and Higher Education // Higher Education Quarterly. 2007. Nr 2. P. 73-84

12. Blinova T. N., Fedotov A. V. Enhancing Access to Higher Education Through University Government Cooperation // : . 2019. . 23, 5. . 12-21

13. ??A?.?ʬs?uGNVivoV?O? p [M]. kF???X. 2017N. 4?. 460?

14. Ryan M. Making Visible the Coding Process // Issues in Education Research. 2009. Vol. 2. P. 142-159

15. Rademaker L. L., Grace E. J., Curda S. K. Using Computer-Assisted Qualitative Data Analysis Software to Reexamine Traditionally Analyzed Data // The Qualitative Report. 2012. Vol. 17, Article 43. P. 1-11

16. ?PA?ڡA??. oꗬ ?a?G_ I{. 猤. 2018N. 48, 4. 70-76?

17. mn??.R. ?. wV----ZINAs ˆ㞓InʁAK?O?zѡeMn. ??AqU?. kF lwoŎ. 2014N. 3 ?. 604?

18. ?O, ?, h. _?: EꗬwI?D ]?, ?DW:CʑwoŎ, 2017N. 33?D@241?

19. ?. l??B?tmOz?G?_oꗬ ?Yz. . 2019. 1. 16-21?.

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