CHAPTER 4: ATTRIBUTES AND MOBILITY OF FEMALE ELITE IN CHINESE
5.1 An inferential statistical analysis (bivariate)
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TESTING THE RELATIONSHIP BETWEEN ATTRIBUTES OF CHINESE FEMALE ELITE AND TYPES OF MOBILITY
5.1 An inferential statistical analysis (bivariate) 5.1.1 Test of Independence
Two variables are related if their attributes vary together, for graduation of this relationship, the statistical of contingency has been used. When purpose of the study is the search for causal relationships, the percentages are estimated only in the direction of the independent variable. This variable is often placed on the columns, and the dependent variable in the ranks; but in this case the high number of attributes of the independent variable discourages its location in the columns, the percentages are horizontal and comparisons are vertical
Albeit illustrative, reading percentage is insufficient. An accurate statistical supplement to graduate the association between the variables and their significance is necessary. In this case, a test of independence has been used to measure the relationship between variables, namely, to test the hypothesis.
1. Hypothesis: There is a relationship between nationality and mobility rate.
Non-Han women have a higher mobility rate than Han women.
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Table 5.1 Relation of mobility and nationality
Low Mobility High Mobility Total
Han 85,366 80,000 83,333
Non Han 14,634 20,000 16,667
Total 100 100 100
Source: my own elaboration
Table 5.2 Test of independence (nationality and mobility)
Chi-square (Observed value) 0,322
Chi-square (Critical value) 3,841
GL 1
value-p 0,570
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 57.04%
2. Hypothesis: There is a relationship between birthplace (province) and mobility rate.
Women from East provinces have a higher mobility rate than women from others provinc
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Table 5.3 Relation of mobility and province
Low Mobility High Mobility Total
Heilongjiang 2,439 0,000 1,515
Beijing 4,878 0,000 3,030
Gansu 2,439 0,000 1,515
Fujian 2,439 4,000 3,030
Shaanxi 2,439 0,000 1,515
Guangxi Zhuang Autonomous Region 2,439 0,000 1,515
Taiwan 0,000 8,000 3,030
Inner Mongolia Autonomous Region 0,000 4,000 1,515
Shanxi 0,000 4,000 1,515
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Table 5.4 Test of independence (province and mobility)
Chi-square (Observed value) 32,204
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 15,22%
3. Hypothesis: There is a relationship between educational level and mobility rate.
Women with a higher educational level have a higher mobility rate than women with a lower educational level.
Table 5.5 Relation of mobility and level of education
Low Mobility High Mobility Total
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Table 5.6 Test of independence (educational level and mobility)
Chi-square (Observed value) 4,406
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 35,39%
4. Hypothesis: There is a relationship between major and mobility rate. Women with a major in natural science and engineering have a higher mobility rate than women with a major in social sciences and humanities.
Table 5.7 Relation of mobility and major
Major
Low Mobility
High
Mobility Total
Social sciences and humanities 41,463 52,000 45,455
Natural science and engineering 43, 902 40,000 42,424
No college education 0,000 4,000 1,515
Missing values 14,634 4,000 10,606
Total 100 100 100
Source: my own elaboration
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Table 5.8 Test of independence (major and mobility)
Chi -square (Observed value) 3,731
Chi-square (Critical value) 7,815
GL 3
value-p 0,292
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 29,20%
5. Hypothesis:There is a relationship between Party school experiences and mobility rate. Women with no-Party school experiences have a higher mobility rate than women with a major in social sciences and humanities.
Table 5.9 Relation of mobility and Party school studies
Low Mobility High Mobility Total
Non party school studies 56,098 40,000 50,000
Party school studies 43,902 60,000 50,000
Total 100 100 100
Source: my own elaboration
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Table 5.10 Test of independence (Party school studies and mobility)
Chi -square (Observed value) 1,610
Chi -square (Critical value) 3,841
GL 1
value-p 0,205
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 20,45%
6.1 Hypothesis:There is a relationship between party work and mobility rate.
Women with Party work experiences have a higher mobility rate than women without.
Table 5.11 Relation of mobility and party work experience
Low Mobility High Mobility Total
Non Party work 36,585 40,000 37,879
Party work 63,415 60,000 62,121
Total 100 100 100
Source: my own elaboration
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Table 5.12 Test of independence (Party work and mobility)
Chi-square (Observed value) 0,322
Chi -square (Critical value) 3,841
GL 1
value-p 0,570
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 57,04%
6.2 Hypothesis: There is a relationship between government work and mobility rate.
Women with government work experiences have a higher mobility rate than women without.
Table 5.13 Relation of mobility and government work experience
Low Mobility High Mobility Total
No government work 34,146 36,000 34,848
Government work 65,854 64,000 65,152
Total 100 100 100
Source: my own elaboration
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Table 5.14 Test of independence (Government work and mobility)
Chi -square (Observed value) 0,024
Chi -square (Critical value) 3,841
GL 1
value-p 0,878
alfa 0,05
Source: my own elaboration Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 87,82%
6.3 Hypothesis: There is a relationship between industrial bureau/finance work and mobility rate. Women with industrial bureau/finance work experiences have a higher mobility rate than women without.
Table 5.15 Relation of mobility and firm/finance/ industrial bureau experience
Low Mobility High Mobility Total
Non firm/finance/industrial bureau 78,049 60,000 71,212
Firm/finance/industrial bureau 21,951 40,000 28,788
Total 100 100 100
Source: my own elaboration
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Table 5.16 Test of independence (Firm/ finance/ industrial bureau and mobility)
Chi -square (Observed value) 2,468
Chi-square (Critical value) 3,841
GL 1
value-p 0,116
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 11,62%
6.4 Hypothesis: There is a relationship between expert work and mobility rate. Women with expert work experiences have a higher mobility rate than women without.
Table 5.17 Relation of mobility and expert work experiences
Low Mobility High Mobility Total
Non Expert work-0 85,366 88,000 86,364
Expert work-1 14,634 12,000 13,636
Total 100 100 100
Source: my own elaboration
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Table 5.18 Test of independence (Expert work and mobility)
Chi -square (Observed value) 0,092
Chi -square (Critical value) 3,841
GL 1
value-p 0,762
Alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 73,23%
6.5 Hypothesis: There is a relationship between ideology and propaganda work and mobility rate. Women with ideology or propaganda work experiences have a higher mobility rate than women without.
Table 5.19 Relation of mobility and ideology work experiences
Low Mobility High Mobility Total
Non ideology work 78,049 84,000 80,303
Ideology work 21,951 16,000 19,697
Total 100 100 100
Source: my own elaboration
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Table 5.20 Test of independence (Ideology and mobility)
Chi -square (Observed value) 0,348
Chi -square (Critical value) 3,841
GL 1
value-p 0,555
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 55,54%
6.6 Hypothesis: There is a relationship betweenPLA/police work/law work and mobility rate. Women with PLA/police work/law work experiences have a higher mobility rate than women without.
Table 5.21 Relation of mobility and PLA/police/law work experience
Low Mobility High Mobility Total
Non PLA/police/law 92,683 92,000 92,424
PLA/police/law 7,317 8,000 7,576
Total 100 100 100
Source: my own elaboration
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Table 5.22 Test of independence (PLA/ police/ law and mobility)
Chi-cuadrado (Observed value) 0,010
Chi-cuadrado (Critical value) 3,841
GL 1
valor-p 0,919
Alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 91,90%
6.7 Hypothesis: There is a relationship between mass organizations work and mobility rate. Women with mass organizations work experiences have a higher mobility rate than women without.
Table 5.23 Relation of mobility and mass organization work experience
Low Mobility High Mobility Total
Non Mass organization 46,341 36,000 42,424
Mass organization 53,659 64,000 57,576
Total 100 100 100
Source: my own elaboration
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Table 5.24 Test of independence (Mass organization and mobility)
Chi -square (Observed value) 0,680
Chi -square (Critical value) 3,841
GL 1
value-p 0,410
alfa 0,05
Source: my own elaboration
Interpretation of the test:
- H0: rows and columns of the table are independent.
- Ha: there is dependence between rows and columns of the table.
- Since the calculated p-value is greater than the significance level alpha = 0.05, null hypothesis H0 can´t be rejected.
- The risk of rejecting the null hypothesis H0 when it is true is 40,96%
5.1.2 Other statistical methods of data analysis
For the purpose of testing the relationship between attributes of Chinese female elite, as a whole, and types of mobility several statistical methods could be used, such a multivariate regression analysis. However, since the data gathering has been coded as a binary system, the most suitable statistical method is the logistic regression analysis or so-called logit model. It is a multivariate method for dichotomous outcome variables.
The findings of the research using the logit model were similar to those presented above with the test of independence, the absence of a significant relationship among the variables. The research only included the results of the test of independence to avoid reiteration of information, and choose the tests of independence because they provide the same information by variable and secondary information such as thecontingency tables.
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CONCLUSIONS
6.1 Answering the research question and secondary information
The research started from the hypothesis that attributes or characteristics of an elite (in this case a female elite group), as well as the organizational structure (in which these women develop their career) and political connections affect their political mobility. This central hypothesis rose from an exploratory analysis, based on the literature review and on a univariate descriptive analysis. And, the research continued to search for a causal relationship; an explanatory analysis of types of political mobility in terms of attributes of female elite.
The research did not find evidences that support the main hypothesis. Attributes of female elite do not influence or have a causal relationship to mobility type. The several tests of independence conducted show that there is no relationship between the type of mobility (low and high) and the attributes of female elite (the various variables examined) along the period of institutionalization of Chinese politics. The research has only got descriptive answers, as the common factors among them (see Table 6.1 at Appendix C).
Regard to the key factors to their promotion mentioned, the study demonstrates that the characteristics among women with low and high mobility are similar, therefore there is no a key factor to their mobility.
As far as other objectives or secondary information that the study included, several information must be noticed. First at all, the proportion of female in the Chinese political elite from 1997 to 2017 tends towards stabilization in a number close or inferior to 10% of the total members, as Table 3.1 (reproduced in next page again) shows.
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Table 3.1 Average (%) of female in the CPC (15th to 18th) Central Committee
15th Central Committee 7,3%
16th Central Committee 7,6%
17th Central Committee 10%
18th Central Committee 8,7%
Source: data derived from Chinavitae.com, statistics of my won elaboration.
The most common attributes among female elite or the standard profile is a Han woman from an East region province or bordering province, with a Master´s degree, a major in social sciences and humanities, with party school studies or not (the percentage is 50%-50%), with work experiences mainly in mass organizations, party and government bodies.
Regarding to the mobility rate of female elite, this can be classified into two types:
low mobility, under the 0,013 rate and, high mobility above the 0,013 rate. The low mobility type is more common among the female elite members, two thirds of women at CC have a low mobility rate
Nevertheless, it showed that the main characteristics of female mobility pattern is age. The study indicates that the mobility rate over time is decreasing, because women are being promoted when they are older than they used to be. Women promoted in the last CC needed more time (years) to get to the same status position than the early CC female members.
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6.2 A Double Glass Ceiling?
The exploratory analysis of data and literature available shows the presence of four characteristics that concur to the existence of a “glass ceiling” in Chinese politics.
The first one, a gender difference that is not explained by other job-relevant characteristics of the employee has been proven by the collection of educational background information on female elite displayed in the four chapter of this research. After analyzing the data gathered, findings prove that female elite members fulfill the requisites of entry in the Party-state; a la large proportion of the female cadres have a high level of education and they engage in the Party at a young age. So, the gender difference cannot be explained in terms of job-relevant characteristics of the employee.
The three remaining characteristics: a gender difference that is greater at higher levels than lower levels of the organization, a gender inequality in the chances of advancement into higher levels and a gender inequality that increase over the course of a career, are proven to be true as it is shown above (Table 1.1) in the analysis of member in CPC institutions from 1977 to 2013. Female cadres are underrepresented in high level power positions, this underrepresentation is greater at higher levels than lower levels of the CPC’s organization chart and the gender inequality increases over the course of a career.
An example of how gender inequality increases over the course of a career is the retirement system that penalized women. Female cadres must retire at an earlier age than male cadres.
The current retirement system shortens the career period of female cadres and implies that over the end of their career they will have less chances to promote or to get up in echelons of the Party-state.
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Table 1.1 Average (%) female-male in CPC institutions (1977-2013)
Average (%) female-male in CPC institutions (1977-2013)
CPC institutions Proportion of women Proportion of men Politburo Standing
Committee
0% 100%
Politburo 2,7% 97,3%
Central Committee 5,2% 94,8%
State Council 6,3% 93,7%
Source: data derived from (Sissokho, 2014) and my own elaboration.
The present study confirms the existence of a “glass ceiling” in Chinese politics and identifies other potential discrimination that women face. The examination of their career histories indicates that women are not eligible to hard power position spheres. They develop their career mainly working in mass organizations as the CYL, ACWF, trade unions and sports related organization. They are almost nonexistent in People´s Liberation Army (PLA), police and the justice system. The profile of expert or dedicated to economic matters is also minority among them.
So, I propose the idea of a double glass ceiling as metaphor of the double discrimination female cadres suffer at CPC. They are not only less likely to promote but also, less likely to work in power capacity areas.
I have also noticed that women are getting elected to CC in an older age than they used to be. Given that one of the requirements of the political institutionalization is age,
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the possibilities of these women to achieve higher positions in the CPC (PSC and PB) are lower.
According to Marie C. Wilson´s statement (2007) about the pipeline theory of women´s ascendancy in her book Closing the leadership gap, the most effective solution to break the glass ceiling is “to insert enough women at all levels and their promotion to higher ranks will be statistically inevitable”.
Currently the number of women in low ranks is too small to increase their statistics chances to promote. This is due to a several reasons: first, the number of women affiliated to the CPC make up only the 23, 3% of total members, and second, the affirmative actions developed by the party-state have been inadequate, as the quotas. Regulations related female quotas often advised to have a minimum number of women in the government or CPC bodies. Cadres in charge of appointments often take these regulations literally and only select the minimum number of women required.
A solution has to address both issues: getting a higher number of women affiliated to the CPC, and evaluate the effectiveness of the affirmative actions. To create parity in the party base in all areas, understood as all bodies within the party-state and all spheres of power, is the key to break the “double glass ceiling”.
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REFERENCES
Afshar, H. (1996). Women and politics in the Third World. London: Routledge.
Alvarez, M. (1998). Mujer y poder en Cuba. Temas Vol 14, 13-25.
Bian, Y., Shu, X., & Logan, J. (2001). Communist Party Membership and Regime Dynamics in China. Social Forces, 805-841.
Bo, Z. (2002). Chinese Provincial Leaders: Economic Performance and Political Mobility since 1949. Armonk, NY: M. E. Sharpe.
Bo, Z. (2007). China´s elite politics. Political transition and power balancing. Singapore:
World Scientific Publishing Company.
Bryant, G. (1984). The Working Woman Report: Succeeding in Business in the 80s. New York: Simon and Schuster.
Chow, G. (2004). Economic reform and growth in China. Annals of economics and finances, 803-841.
Chow, N.-L., Zhang, N., & Wang, J. (2004). Women´s Studies and and Sociology of Women/Gender in Contemporary China. Gender & Society, 161-188.
‧ 國
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‧
N a
tio na
l C h engchi U ni ve rs it y
76
Cotter, D. A., Hermsen, J. M., Ovadia, S., & Vanneman, R. (2001). The Glass Ceiling effect. Oxford Journals, Vol. 80, Issue 2, 655-681.
D´Ancona, C. (2001). Metodologia cuantitativa: estrategias y tecnicas de investigación social. Madrid : Síntesis.
Davin, D. (1976). Woman-work: women and the Party in Revolutionary China. Oxford:
Clarendon Press.
Diaz, E., & Caram, T. (1996). Mujer Cubana, Desarrollo Social y Participacion. Revista Mundial de Sociologia, No.2.
Dickson, B. (2010). Dilemmas of party adaptation. In P. Hays, & S. Rosen, Chinese politics.State, society and the market (p. 22-40). USA: Routledge
Dittmer, L. (1995). Chinese informal politics. The China Journal, No. 34.
Dreyer, J. T. (2000). China´s political system: modernization and tradition. Boston:
Pearson Longman.
Dye, T. R. (1976). Who´s running America? En T. R. Dye, Who´s running America?
(pág. 12). New Jersey: Prentice Hall.
Gilbert, S. (1973). The emancipation of Chinese Women. World Politics, 55-79.
Gilmartin, C. (1993). Gender in the formation of a Communist body politic. Modern China, 299-329.
‧ 國
立 政 治 大 學
‧
N a
tio na
l C h engchi U ni ve rs it y
77
Goldstein, A. (1994). Trends in the study of political elites and institutions in the PRC.
The China Quarterly, 714-730.
Goodman, D. (2004). Why women count: Chinese women anf leadership of reform. In Chinese women: living and working (p. 19-41). London: In McLaren .
Guo, X., & Zhao, L. (2009). Women´s Political Participation in China. East Asian Policy, 50-60.
Guo, X., & Zheng, Y. (2008). Women´s political participation in China. China Policy Institute, 1-13.
Hershatter, G. (2004). Women in Chinas Long Twentieth Century. Journal of Asian Studies, 991-1065.
Hoffmann-Lange, U. (2006). Methodological developments in elite research. The 20th IPSA World Congress. Fukuoka.
Howell, J. (1998). Gender, Civil Society and the State in China. In V. Randall, & G.
Howell, J. (1998). Gender, Civil Society and the State in China. In V. Randall, & G.