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Abstract

The Chinese educational system operates on a chain relationship, where primary education acts as a gateway to better secondary education. This, in turn, increases the likelihood of attending a reputable high school, ultimately leading to a higher probability of gaining admission to a prestigious university. Consequently, primary schools, particularly key schools, represent a significant and influential market at the initial stage of the educational journey. The decision and selection process for a primary school are influenced by three types of capital: cultural capital, economic capital, and social capital. And in order to explore the predominant factors influencing access to a key primary school, this quantitative study has been conducted through questionnaires aimed at 1,082 Chinese students hailing from 21 universities across China. The findings of this study indicate that social capital, cultural capital and economic capital play pivotal roles in predicting access to a key primary school. In this sense, influential variables such as extracurricular activities, purchase housing, mother's education and social relationships have been identified. But it is important to note that both parents do not exert equal influence in this regard, with the mother emerging as the primary determining factor. In essence, the mother wields more influence than the father when it comes to selecting a primary school for their children.

Keywords

cultural capital economic capital social capital school choice

Introduction

The way the Chinese education system is set up favors the presence of market mechanisms through which parents invest their resources to provide the best educational opportunities for their children (Liu & Apple, 2016). The two main aspects of this system that enable the presence of these mechanisms are a focus on entrance exams for senior high school and university, and the existence of different types of educational centers categorized by academic reputation (Doncel Abad, 2018). In relation to the official channels to enter education centers, according to Chapter 5, Article 26, of the law on compulsory education of March 14, 1992, in Compulsory Education, the assignment of schools to students is based on the area of residence in which the school is located and on the Hukou, which is a household registration system that groups individuals into families and links them to their location (Wang, 2005). The Hukou system also classifies individuals and family groups as rural or urban, local or non-local. This classification determines the type of benefits individuals can access basic social coverage such as healthcare, employment, and education (Duhalde Valenzuela, 2021).

Officially, there are two general types of centers, public and private (Doncel Abad, 2018), which, in turn, can be subdivided. The private ones are classified into two subtypes, for-profit and nonprofit. Among private centers, there are important differences in prestige between private schools for immigrants in cities and private centers aimed at a small economic elite (Doncel Abad, 2018). Public centers are also subdivided into two types: regular schools and key schools. In this general group, the key schools have a stronger reputation, among other things, because their students graduate with higher transition rates from compulsory to post-compulsory education (Liu & Apple, 2016). And despite the fact that the government officially abolished the existence of key schools as such in compulsory education, this qualitative disparity between public schools still persists. However, it should be noted that, once the period of compulsory education is over, entrance exams come into play in the transition to the post-compulsory stage. The first of these, the Zhongkao (the Senior High School Entrance Examination), is taken to move from compulsory secondary school to senior high school. The second, the Gaokao (the Nationwide Unified Examination for Admissions to General Universities and Colleges), links the path from senior high school to university. The scores in both exams determine the possibilities of attending the best education centers later on.

Under this configuration, the first step of the educational path desired by parents for their children is to attend a key school in primary education, to increase their chances of getting a good score on the Zhongkao exam. The second step will consist of getting into a key school in high school, pursuing the same objective of obtaining good training for the Gaokao exam. Throughout the educational path one can go through different types of schools, but the vast majority of parents believe that it is crucial to choose a good primary school to start the path to educational success with the best possible guarantees.

While the school district, place of residence and a test score are the official entrance criteria, as mentioned above, the very configuration of the educational system as a quasi-market, leads to competition among parents to gain advantages in getting into the best schools (Liu & Apple, 2016). Consequently, getting into a good school is not only a matter of Hukou or meritocracy, but also of “parentocracy” (Gopinathan & Lee, 2018; Zhao et al., 2018). In other words, along with the criteria of residence and academic skills, other factors such as wealth, friendship networks and the parents’education come into play in the struggle to get into the best schools (Lee & Morris, 2016).

Bourdieu (1986) identifies different types of family resources or types of capital present in any system where market mechanisms operate, namely: economic capital, cultural capital and social capital (Liu & Apple, 2016).

Research has shown that economic capital is an element that conditions the educational trajectories of Chinese students. As exemplified by Fang and Feng's study in 2018, empirical evidence underscores the substantial and favorable influence of family income on the educational achievements of secondary school students. Notably, a direct correlation emerges, whereby the higher the income of parents, the greater the scholastic success attained by their children. Similarly, Zhang and Han (2018) conclude that the better the economic situation of a family, the higher the school life expectations of their children. Wang and Huang (2021) also confirmed the univariate correlation between economic capital and higher education gains was significant (r = 0.113, p < 0.01). In relation to the choice of education centers, Fang (2005; 2011) points out that family economic capital has a positive correlation (r = 0.213, p < 0.01) with the note of examen of the children and the given education center according to Pearson Correlation, and this association has been found at any stage and educational level in China. In this sense, families of high socioeconomic status can opt to choose better schools for their children through different mechanisms such as:“paying sponsorship fees”, by “Hukou transfer”or “by home purchase” in the school district of the key school (Fang, 2005, 2011). These results are also supported by the work of He (2019). In addition, both authors, Fang and He, show how families with greater economic resources are more predisposed to invest their money in their children’s education, as they consider the educational success of their children as a necessary path to strengthen their social status. Thus, the children of these families often engage in extracurricular activities related to art, painting, dance, sports, and telecommunications, which are considered as another shortcut to facilitate access to prestigious fine arts universities (Fang, 2005, 2011; He, 2019).

Social capital is important in any society, but in China it is especially relevant (Wu, 2013). Social capital consists of actual or potential resources that are generated from interactions and exchanges between individuals (Bourdieu, 1986). In the particular case of China, the concept of social capital is closely related to the concept of guanxi. As a form of social capital, guanxi refers to a network of contacts that an individual can draw on to obtain resources or advantages in their social life (Bian, 2006; Qi, 2013). Thus, the occupations held by parents are important because they create a certain social network. In other words, the social network created by a manager of a large company or a senior state official offers different options to that of a peasant. For example, He (2019) found that the proportion of children enrolled in elite schools whose parents had professional or managerial occupations was significantly higher than that of children whose parents were manual laborers.

Cultural capital can be possessed in different ways according to Bourdieu (1997): embodied (disposition of the parents’ thought and behavior towards the educational process), objectified (cultural assets such as the number of books in the home), and institutionalized (official certificates of the level of study attained by the parents). For example, the educational experiences and personal histories of the parents inevitably influence the extent and effectiveness of their involvement in the choice of schools for their children. In this regard, research consistently shows that the education of parents is an important factor influencing their children’s school experience, and that the higher the level of parental education, the greater the association (Bourdieu, 1986; Bourdieu, 1997; Gao, 2011; Lu et al., 2021). For example, scientific evidence shows that the greater the number of years of schooling that the parents have had, the greater the number of years of schooling their children will have (Fang, 2005; Huang et al., 2016; Li, 2003; Lin & Zhang, 2015; Liu, 2008; Yang & Zhou, 2013; Zou & Ma, 2019). Even more, according to the research of Mao (2022), parental involvement had an indirect effect on children’s learning behaviors. The research finding of Yu et al. (2022) also showed that the academic achievement of junior high school students can not only be improved by increasing the family cultural capital, but also by enhancing parent support for academic participation, raising educational expectations for students' development, and cultivating students' good learning attitudes. School choice research shows that parents with higher educational attainments are more involved in making decisions regarding their children’s school careers. For example, they have a greater inclination to invest in their children’s education, to create a better environment for their children’s upbringing at home, and, in particular, they are more likely to get involved in choosing the best possible school (Wang & Shi, 2014; Zhao & Hong, 2012).

In sum, after reviewing the literature, it can be observed that Bourdieu’s approach to facilitate measuring the different types of resources employed by parents has been widely applied to analyze the influence of family background on the school experience of students in China (Shi & Li, 2018). Similarly, it can also be seen that the cultural capital of families has been the most researched factor of family background, but that further work is still needed to understand the influence of these three capitals in a comparative way. For these reasons, we adopted this theoretical approach in the present research and set as an objective to determine the importance of the different economic, cultural and social capitals in accessing key schools in primary education.

The question that gives rise to the present research is: how does the combined presence of different family capitals affect the probabilities that a student will enter a key school in primary education?

Analysis Model

Based on the theoretical approach presented in the previous section, we set up the analytical model. We are interested in finding out about the educational trajectories of a sample of university students, specifically, we want to discover what factors have determined the start of this academic trajectory. The fact that they are university students allows us to ask about the academic path they have already followed, which on this occasion, we focus on the beginning of the same, on access to primary school.

In this sense, we relate the economic, social, and cultural capital that parents possess to the condition of their children having attended a key school in primary. We measure economic capital through the following two variables: purchase a home in the school's catchment area and the number of extracurricular activities undertaken. The concept of social capital is linked to the variables: occupation of the father and mother and access to school through social relations. And we operationalize cultural capital through the variables: level of education attained by the parents and the number of books at home.

Besides, we add different control variables to the model of analysis through which we intend to assess the effect of family social background on access to a key primary school, without the possible effects of the individual's own personal characteristics. We have taken this decision because there are other elements that can determine how parents invest their capital in promoting their children's educational trajectories, such as gender (Liu, 2016; He et al., 2018), the number of siblings (Bian, 1996; Tsui & Rich, 2002; Veeck et al., 2003; Lee, 2012; Liu, 2016), or whether their mother tongue is the same as the language used in the educational system (Kong, 2016). The model we test is the following Figure 1:

Figure 1.

Analysis Model.

In summary, our aim is to find out how the parent’s economic, social, and cultural capital have influenced the attainment condition of having attended a key school at the primary school, considering other characteristics of the individual such as gender, number of siblings and whether he/she speaks Putonghua. This model takes two specific forms, a basic model, and an extended model. In the first model, we include the explanatory variables and the dependent variable. In the second one, we also introduce the control variables, since in the light of the literature we consider that they can condition the investment of family resources in the schooling of their children.

Hypothesis

In order to achieve the general objective, we have proposed a set of hypotheses with which to test how each of the capitals independently, and all together, influences entering a key school. In this way we can determine the relative influence of each of the capitals. General hypothesis: economic, social and cultural capital influence entering a key school in primary education.

(i) Economic capital:

Sub-hypothesis: A greater number of extracurricular activities performed influences access to a key school.

Sub-hypothesis: The purchase of housing in the school area influences access to a key school.

(ii) Cultural capital:

Sub-hypothesis: The number of books in the home influences access to a key school.

Sub-hypothesis: The father’s educational level influences access to a key school.

Sub-hypothesis: The mother’s educational level influences access to a key school.

(iii) Social capital:

Sub-hypothesis: Social relationships influence access to a key school.

Sub-hypothesis: Father’s occupation influences access to a key school.

Sub-hypothesis: Mother’s occupation influences access to a key school.

Methodology

Sample

In order to maximize the sample size, convenience sampling was carried out, targeting the population of university students. This profile was selected because it allowed us to trace the educational trajectories of students from elementary school to university studies through their responses to the questionnaire. A total of 1,082 Chinese students from 21 universities in different provinces throughout the country voluntarily participated in this research. Specifically, the questionnaire was administered in the following provinces and municipalities in China: Tianjin, Shanghai, Hubei, Zhejiang, Jiangsu, Heilongjiang, Jilin, Sichuan, Gansu, Hebei and Macau (see Figure 2) in 2018.

Figure 2.

Chinese provinces participating in the sample.

The ages of the final sample participants ranged from 17 to 30 years. Among them, 77.7% were females and 19.4% males (see Table 1). The sample is skewed primarily for three reasons: First of all, according to statistical data published by the National Bureau of Statistics (2021), in higher education, both at the undergraduate and master's levels, the female population (51%) has surpassed the male population (49%). Secondly, the authors have had more access to distribute the questionnaire in foreign language faculties, where the female population is tin the majority. Thirdly, due to the difficulties in carrying our research in China, and particularly in carrying out large-scale surveys, we decided to carry out a convenience sample method, although, this implies a case selection bias. The survey, on which several of the contributions are based, involved interviews with 1,082 university students, at locations thoughout China. Given the size of our survey, and the detailed information about parental involvement in the choice of overseas study topics, we maintain that the contributions provide novel, and even unexpected, insights into the reality of contemporary study abroad choices by Chinese students and their parents.

Table 1.

Profile of the sample of university students by age and sex.

Age	Sex*	Count	% of N columns
17-25 years old	female	831	80.1%
	male	206	19.9%
	total	1037	100.0%
26-30 years old	female	10	71.4%
	male	4	28.6%
	total	14	100.0%

*Note: 31 cases missing by system.

Instrument

The questionnaire was designed specifically for this research. The blocks of questions were articulated according to the following theoretical aspects: educa-tional and professional orientation, cultural capital, eco- nomic capital and social capital. The operationalization of each concept was carried out on the theoretical and empirical basis collected in the following works: Gao (2011); Wu (2013); Wang and Shi (2014); Sheng (2015); Liu and Apple (2016) and Kim et al. (2016).

Once the concepts were operationalized, extensive consultation work was carried out. First, after designing the questionnaire, it was sent to researchers specializing in Sociology of Education for evaluation. Then it was translated into Mandarin, but before its application, three pre-tests were conducted to reduce the biases related to the meaning of the translation of the questionnaires.

Procedure

The questionnaire was administered in two modalities: face-to-face and on-line, between the months of November and December, 2018. In both modalities, the subjects were informed that the test was anonymous and were informed that they were taking part in research on educational and career guidance in China’s educational system. The face-to-face survey was administered to the students by team members at the various university campuses. Each questionnaire was given a code to ensure the anonymity of each student. For the online version, the SOJUMP survey program was used. The protocol for administering the on-line questionnaire was carried out through a meeting with the heads of the universities in China and the person responsible for the on-line platform. Once the questionnaire was developed, a QR code was created, which was then sent via the Wechat platform. Participants had one week to fill in the questionnaire. The data collected online was conducted also through SOJUMP, a platform where surveys, tests and online voting are conducted publicly and freely, which is accessible via a link to its URL. This platform guaranteed the anonymity of the participants at all times.

Variables

Based on the literature consulted, the variables were operationalized as follows:

Dependent variable

Enrolled in a key school. This is a dichotomous variable that indicates the quality of being enrolled in a key school for primary education, coded with = 1, or not being enrolled, which is coded with = 0.

Predictor variables

Economic capital

Economic capital is usually consid- ered as the economic income of the family (Fang & Feng, 2018), but investment in education is also taken as an indicator of economic capital (Fang, 2005, 2011; He, 2019). Taking investment as a reference, we adopt extracurricular classes and the purchase of a house in the catchment area of the educational insti- tution as indicators of economic capital.

(i) Extracurricular Activities: In works that analyze the dynamics of social reproduction in the Chinese education system, it is common to find school activities as an indicator of parents’embodied cultural capital or of their predisposition to become involved in their children’s educational process (Gao, 2011; Lu et al., 2021). However, it is a practice that depends on economic capital, above all, because of the cost involved in carrying out each of them. For this reason, we consider extracurricular activities as an indicator of economic capital. A total of 13 different types of popular extracurricular classes in China were collected in the questionnaire, such as: ballet classes, poetry, calligraphy, chess, musical instruments, drawing, sports, English, Math, and so on. From the answers we have created a cumulative index, if the respondent had not attended any of them it was coded with a zero and if they attended all of them, it would be coded with 13 points.

(ii) Home purchase: One of the official criteria for admission to a key school is to have a home in the school’s area of residence. For this reason, in the absence of this condition, some parents buy homes in these districts to meet this requirement. For this reason, a dichotomous variable was used as an indicator, indicating with a 1 if they bought a house in the area of the school with the main purpose of increasing the likelihood of the child being admitted to a school, and with a 0 if they did not buy a house in the area of the school.

Social capital

The selection of indicators, here, is conditioned by the uniqueness of the cultural context of China, where social relations are determined by the guanxi possessed by individuals. Guanxi, as a form of social capital, refers to a network of contacts that an individual can draw on to obtain resources or advantages throughout life (Bian, 2006). In fact, guanxi is perceived as a currency of exchange, of a resource from which reciprocity is expected once activated. For this reason, in the Chinese cultural context, the occupation held by parents is a relevant factor in creating one social network or another. For example, the director of a public company will develop a certain social network and a farmer will create another type of network, both in accordance with their occupations. Consequently, the following have been defined as indicators of social capital:

(i) Father’s and mother’s occupation: The occu- pation of the parents was coded according to the International Standard Classification of Occupa- tions 2008 (ISCO-08) . The variable was coded into three cate- gories. 1 = Laborers (OC5 to OC8), 2 = Tech- nicians (OC3 to OC4) and 3 = Professionals and Managers (OC1 to OC2).

(ii) Accessing an educational center through social relations: This is a variable applied, for example, in the study by He (2019). On this occasion we adopted as an indicator a dichotomous variable in which the condition of having accessed an educational center - of any type - through social relations is associated with a value of 1, and not having accessed one through social relations with a value of 0.

Cultural capital

Two traditional variables used in this kind of research are taken into account here: parents’ educational level and the number of books in the home OECD (2017).

(i) Maximum level of education attained by the father or mother: This variable has been coded into four categories. 1 = up to primary school; 2 = Compulsory secondary school; 3 = Higher secondary school and 4 = university.

(ii) Number of books in the household: It is a variable coded according to the number of books in the respondent’s household, applying a scale with the following cut-off points: 1 = 0-10 books; 2 = 11-25 books; 3 = 26-100 books; 4 = 101-200 books; 5 = 201-500 books and 6 = more than 500 books (MECD, 2014).

Control variable

Gender

The gender variable was coded as a dichotomous variable. Female = 1; Male = 0. We included this variable to test whether gender conditions parents’ investment in their child's schooling (Liu, 2016; He et al., 2018).

Putonghua

The Putonghua (Standard Mandarin) variable was coded as dichotomous variable. Yes = 1; No = 0. Putonghua is the language of instruction in schools. Putonghua is not spoken in rural areas, except in school. And parents in rural areas had limited involvement in their children schooling (Kong, 2016). So, we think can conditioned the access to a key school.

One-child

The one child variable was coded as dichotomous variable. Yes = 1; No = 0. Research in this regard indicates that the one-child policy has had an unintended consequence, especially in urban settings, by fostering a culture centered on children and their education, regardless of gender (Bian, 1996; Tsui & Rich, 2002; Veeck et al., 2003; Lee, 2012; Liu, 2016).

Analysis technique

Since the objective is to obtain a mathematical formula that serves to calculate the probability of the event studied in a new individual due to the values of the variables included in the model, we looked for a model, among all the possible ones, that would be the most economical. In other words, a model in which the smallest number of possible (independent) variables generates the most accurate and valid prediction of the evaluated response. In our particular case, we are looking for the most economical model that allows us to ascertain the probability of being enrolled, or not, in a key school in primary education depending on a set of family resources or capital. For this purpose, we use the Logistic Regression technique (García Pérez et al., 2010), which when applied to different independent variables is called Multivariate Logistic Regression (MLR). The most interesting characteristic of this technique is the relationship between the coefficients obtained in the quantification of the occurrence of the event by means of the Odds Ratio (OR).

Logistic regression is represented by the following equation: $P = \frac{1}{1 + e^{- y}}$ (1)

where“y”is the linear model function and“e”is the base of the Napierian logarithms, whose approximate value to the thousandth place is 2.718.

Analysis

In this research, for the analysis and hypothesis testing, we have performed a logistic regression, including all predictors in the model. The main reason for adopting this analysis strategy has been that even if there were non-significant predictors, this information would still be relevant for testing the hypotheses. Data analysis was performed with the SPSS 24.0 statical program version.

The table shows that both models are significant because the Hosner and Lemshow test shows a value greater than or equal to 0.05 (Rodríguez Sabiote & Gutiérrez Pérez, 2007). According to the Nagelkerke R-squared, the explanatory power of the first model is 19.5% and the power of the second model increases to 20.4% because more variables are included in the model. So, these indicators show the goodness-of-fit of both models.

The results for the group of university students we have selected and the conditions under which we have analysed both the basic model, where only the variables defined for the different capitals are brought into play, and the extended model where the control variables are also included, show that social origin, represented in its different capitals, conditions access to a key primary school. But not all the variables included in the models have an influence, and in the cases where they are significant, they have a different influence. In both the basic and the full model, the significant variables are the same, namely: extracurricular activities, buying a house in the school's catchment area, entering through social relations and the mother's educational level. In other words, according to our model these are the only four variables that influence access to a key school.

The following are the main results of the MLR:

Mother's education - Category reference: University level. It has a negative effect B = -1.651 and is the most important independent variable. These data show that the probabilities of being enrolled in a key school in primary education decreases as the mothers' education level decreases. In particular, if the mother has only a primary school education or less, the probabilities of being enrolled in a key school in primary education decreases by 80.8%, if the rest of the independent variables do not change.

Access to school through social relations - Category of reference: No social relations. It has a negative effect B = -0.984 and is the second most important variable. In other words, the fact that parents do not have the social connections to access a key school reduces the probabilities of their child accessing a key school by 63%.

Purchase a house - Category of reference: no buy a house. It has a negative effect B = -0.695 and is the third most important variable. The date shows that the probabilities of entering a key school in primary decrease a 51% when parents can move to the catch area of the school.

After-school index. Access to school through the number of extracurricular activities carried out by the children has a positive effect B = 0.103 and is the fourth most important variable with an Exp(B) = 1.09. That is, when the independent variable varies by one unit (it means having one more extracurricular activity) the relationship of being enrolled changes with a cumulative factor of 1.09. That is, the probability of being enrolled in a key school is multiplied by 1.09 if the other independent variables do not change.

Finally, to achieve the objective of this work, it is important to highlight two relevant results. On the one hand, the two economic capital variables are significant, although the most important are the mother's cultural capital, and the second the guanxi. On the other hand, that the role played by the father in the educational process of his children is less decisive in the cultural dimension. In other words, the cultural capital of the mother plays a more decisive role than the father. The data shows that no variable related to educational level of the father is significant in predicting the probability of accessing a key school in primary education (see Table 2).

Table 2.

Logistic regression: Basic model and extended model.

Variables	Basic model				Extended model
Variables	B	Error estándar	Sig.**	Exp(B)	B	Error estándar	Sig.**	Exp(B)
Extracurricular index	.094	.041	.022	1.098	.103	.042	.014	1.109
Home purchase	−.705	.302	.020	.494	−.695	.307	.024	.499
Mother occupation*			.904				.868
Mother occupation (Laborers)	−.100	.225	.657	.905	−.110	.234	.640	.896
Mother occupation (Technicians)	−.087	.500	.861	.916	−.188	.514	.714	.828
Father occupation*			.660				.975
Father occupation (Laborers)	−.199	.234	.394	.819	−.013	.244	.959	.988
Father occupation (Technicians)	.002	.427	.996	1.002	.083	.442	.851	1.087
Social relations (No)*	−.939	.242	.000	.391	−.984	.247	.000	.374
Mother max of education level			.002				.013
Mother primary or less	−1.817	.505	.000	.163	-1.620	.520	.002	.198
Mother secondary	−.297	.303	.327	.743	−.284	.318	.372	.753
Mother higuer secondary	−.429	.263	.103	.651	−.338	.273	.215	.713
Father max of education level			.843				.798
Father primary or less	−.060	.510	.906	.941	−.235	.533	.659	.790
Father secondary	−.258	.320	.420	.772	−.311	.334	.352	.733
Father higuer secondary	−.080	.264	.761	.923	−.096	.274	.726	.908
N^a Books	.146	.077	.059	1.157	.139	.081	.086	1.150
Gender (Female)*					−.201	.224	.370	.818
Puntunghua (No)*					−.255	.191	.181	.775
One child* (Yes)*					.083	.207	.688	1.087
Constante	.500	.560	.373	1.648	.605	.623	.331	1.832
Number of cases included	729			696
Logaritmo de la verosimilitud -2	795.49			754.57
R cuadrado de Nagelkerke	0.195			.204
Cut off point	0.5			0.5
% of correctly classified cases	68.9%			68.8
Prueba de Hosmer y Lemeshow	.913			.702

*Reference category of the independent variables.

**Significant coefficient at 5%.

Discussion and Conclusion

After analysing the question “what are the probabilities that a student enters a key school in primary education, given the combined presence of the different family capitals?”, the answer is that a greater or lesser probabilities of accessing a key school will depend on a combination of the three capitals, economic, social, and cultural. These results are consistent with other research that highlight how the economic, social, and cultural capital of the family influences the educational trajetory of their children (Gao, 2011; Wu, 2013; Li, 2018; Liu et al., 2020; Lu et al., 2021). Although, in our research, we have found that each one has a different grade of influence. For instance, the most important variable in the model shows that a mother with a primary education or lower level attained reduces the chances of entering a key school, meanwhile the occupation of the father has no significance in the model.

Our results show that achieving access to a key school through market mechanisms is a matter linked to the elite middle classes and mothers. The uniqueness of the behaviour of the Chinese middle classes in the schooling process has been examined in other works, such as those of Yu and Han (2019) and Wang (2020). Furthermore, the central role of mothers has already been presented in the works of Sheng (2015), and Zou and Ma (2019) who point out the differential factor of mothers with high levels of education in the school life of their children, and that the central role is palyed by the mother, as opposed to fathers, reflecting a clear division of gender roles in Chinese society. However, our findings add how the combined effect of the three capitals and the gender role plays by the mothers related to schooling increase the probabilities that their children have been enrolled in a key school Table 3.

Table 3.

Summary of the hypothesis and sub-hypothesis tested.

Capitals		Variables	Model
Sub-hypothesis		Variables	Basic	Extended
Economic capital	1.1	Extracurricular activities	Influence	Influence
Economic capital	1.2	Purchase housing	Influence	Influence
Cultural capital	2.1.	Number of books	No Influence	No Influence
	2.1.	Father’s education	No influence	No influence
	2.2.	Mother's education	Influences	Influences
Social capital	3.1.	Social relationships	Influences	Influences
	3.2.	Father’s occupation	No influence	No influence
	3.3.	Mother’s occupation	No Influences	No Influences
R cuadrado de Nagelkerke			19.5%	20.4%

Finally, it is important to point out that the existence of other intervening factors was not evaluated in the interpretation of the model and it is necessary to keep in mind the sampling method that was used. Furthermore, although the model is in line with the estimates of other authors who have studied accessing schools in China, the process of school choice may be associated with other variables that were not considered here. It could be useful to assess other factors with these variables, for example the interaction of the social relationships of different family members, such as grandparents, the relevance of having been enrolled in a day care center or increasing the sample size.

Supplemental Material

Supplemental Material - “Parentocracy” is “mothercracy”: The mothers as key factor to the access to primary “key schools” in China

Supplemental Material for “Parentocracy” is “mothercracy”: The mothers as key factor to the access to primary “key schools” in China by Jia Lin and David Doncel Abad in International Journal of Chinese Education

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This work is part of the research project - Orientación Educativa y Profesional,formación del capital humano chino en cultura española - funded by the University of Salamanca under reference num- ber PIC2-2020-09 ( https://produccioncientifica.

ORCID iDs

Jia Lin

David Doncel Abad

Supplemental Material

Supplemental material for this article is available online.

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