Education, Party Membership, and Occupational Status Attainment in China's Social Transformation (1950-2017)

Education, Party Membership, and Occupational Status Attainment in China's Social Transformation (1950-2017) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Education, Party Membership, and Occupational Status Attainment in China's Social Transformation (1950-2017) Fuqin Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4591449/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Previous researches on the occupational status attainment among Chinese residents have predominantly employed grouped regression analysis, which categorizes data according to significant historical events. This approach explores how variables such as education and party membership influence status attainment across different time periods. However, it often overlooks the heterogeneity of effects within these groups. To address this gap, the present study utilizes urban sample data from the "China General Social Survey (CGSS)" spanning from 2003 to 2017(n=43,235) 1 . It segments the population into 68 cohorts based on individuals' year of entry from 1950 to 2017, thereby concentrating on the evolving impacts of education level and party membership on occupational status attainment post the establishment of New China. The findings reveal a continuous overall increase in average occupational status since the founding of New China. Both education level and party membership positively correlate with status attainment; however, their relative significance exhibits considerable variation across different eras. These results both corroborate and challenge prior studies concerning status attainment. While the method of grouped regression analysis based on major historical events effectively captures the general shift from a redistributive to a market economy, it fails to sufficiently account for the nuanced impacts of social change on occupational status attainment. This study underscores the need for more detailed analyses to comprehensively understand these dynamics. Social science/Development studies Social science/Sociology Social science/Education Social transformation education level party membership occupational status attainment repeated cross-sectional design Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Since the founding of New China, especially since the reform and opening up, there have been significant changes in the social class structure and intergenerational mobility in China. These changes have attracted substantial attention from both domestic and foreign scholars. The study of social stratification and mobility has thus become one of the most active areas in sociological research. Previous studies have primarily focused on the dynamic changes in the stratification structure, paying less attention to the dynamic changes in mobility opportunities, particularly at the micro level of status attainment processes (Li, Shi and Zhu 2018). The classic status attainment model, known as the Blau and Duncan model, summarizes the mechanism of status attainment as a combination of ascriptive factors (such as parental background) and achievement factors (such as education). It emphasizes that in industrialized societies, the influence of ascriptive factors will gradually decrease, while the role of achievement factors will become the dominant mechanism in a market-oriented society (Blau and Duncan 1967). This logic has been extensively tested in studies of market-oriented countries and has become the foundational model for analyzing social mobility processes both domestically and internationally. However, unlike Western developed industrial societies, the industrialization process in new China is accompanied by the transformation of social systems and distribution rules—from a planned economy system with redistribution rules to a market-oriented system with performance-based distribution. This transformation is achieved under the unified leadership of the Communist Party of China, making China's occupational mobility mechanism a unique mixture of political loyalty and the meritocratic principles of modern occupational mobility. This complexity has led to the market transition theory (Nee 1989) being questioned by many scholars from its inception (Liu 2003 ). Research on market-oriented countries suggests that political inequality based on party membership is central to the hierarchical order in socialist countries. The redistribution of power represented by party membership continues to play a significant role in people's status attainment, especially in the occupational and income status of the bureaucratic class, without showing a downward trend (Bian and Logan 1996; Lin 1995; Parish and Michelson 1996; Rona-Tas 1994; Walder 1995a). In competitive explanations of political capital and human capital, Walder's dual-path theory on the status attainment of Chinese elites is particularly noteworthy. This theory posits that political loyalty (measured by party membership) is the primary condition for becoming an administrative elite, while education is crucial for becoming a professional elite (Walder 1995b). Even after market-oriented reforms, due to the rational need for political stability and economic development, the influence of higher education on becoming administrative and professional elites has significantly increased. However, this dual elite status attainment pattern has not changed significantly, with party members continuing to have advantages in position promotion and resource allocation (Li and Walder 2001). The hierarchical dynamic process model proposed by Zhou et al. (1996) suggests that macro political processes and changes in state policies affect people's life opportunities (education, occupational activities, work organization, career transitions, promotions, income, and housing) and fluctuate over time. The returns on human capital and political capital differ in the redistribution logic of the socialist state system and the performance distribution logic since market-oriented reforms, impacting people's life opportunities differently. The hierarchical dynamic model provides a new analytical perspective for studying changes in the social class structure in transitional China. However, testing the impact of macro political processes or changes in state policies on the stratification mechanism (reflected through period effect comparisons) often relies on insufficient empirical data. Researchers typically divide the development stages of new China into different historical periods and compare the status attainment patterns of different population groups born in the same period or entering the labor market at the same time to reflect changes in the social stratification mechanism across different periods in China. This approach assumes that the effects of different mechanisms (variables) within the same period (group) remain constant, ignoring the heterogeneity of intra-group effects. Unlike previous studies that divide historical stages based on major historical events, this study combines repeated survey data from the "China General Social Survey (CGSS)" from 2003 to 2017 (urban samples). A continuous sample(n = 43235) containing 68 cohorts (1950–2017) was constructed based on people's year of entry. Through a mixed effects model, the study focuses on analyzing the impact of education level (including whether one has received university education) and party membership on people's occupational status attainment. It also examines whether these impacts show different trends depending on the time people entered the labor market, thereby addressing the shortcomings of historical periodization methods. 2. Human Capital, Political Capital, and Status Attainment The status attainment model suggests that in industrialized societies, individuals' occupational status is primarily constrained by ascriptive factors and achievement factors. As the level of industrialization increases, the role of achievement factors in status attainment becomes more significant (Blau and Duncan 1967). This viewpoint has been widely validated in industrialized countries in Europe and America (Erikson and Goldthorpe 1992). In domestic studies on status attainment in China, it has also received support from various research data (Li 2005 ; Xu 2000 ). Despite the rich extensions made by both domestic and foreign research based on the classic status attainment model 2 —such as expanding explanatory and predictive variables and adding structural variables (like social networks) to individual variables (Zhou 2009 )—the core assumptions of the classic model remain unchanged. These assumptions posit that in industrialized countries, social stratification mechanisms are relatively stable across generations and individual life processes. Once historical and cultural factors of different societies are controlled, the intergenerational mobility opportunities between fathers and sons remain constant, known as the "FJH hypothesis" (Featherman, Jones, and Hauser 1975). This hypothesis statistically assumes that the mechanisms of various explanatory variables do not change with structural variables such as time or space. In contrast to the classic status attainment model, which emphasizes that industrial development brings about changes in opportunity structures and leads to the varying roles of family background and human capital in status attainment, the socio-economic development in China since the founding of the People's Republic has gone through different historical stages. China's industrialization process has also been accompanied by a transition from a redistributive economy to a market economy. Each stage exhibits distinct differences in national policies and political processes, including economic development goals, ideology, distribution of educational opportunities, and degree of marketization. Zhou and his research partners argue that compared to market-oriented societies, under the national socialist system, people's life opportunities are not only constrained by the unique redistributive institutions of the state but also significantly influenced by changes in macro political and state policies (Zhou, Tuma, and Moen 1996). Following the model of status attainment, scholars studying the status attainment in China have conducted comparative studies on the relative effects of human capital and family background. While there have been numerous explorations, these studies are often theoretically constrained by the framework of the Blau-Duncan model. A significant theoretical advancement is the exploration of the impact of human capital and political capital on status attainment following the transition from a redistributive to a market economy. Victor Nee introduced the "market transition theory" (Nee 1989), which posits that market and redistributive economies are fundamentally different economic systems, each associated with distinct social stratification mechanisms. The market economy is said to enhance job opportunities and increase market power for individuals with higher education, while diminishing the political power of cadres in the allocation of market resources. This theory has ignited a robust debate among scholars of social stratification regarding the stratification model in transitional states, particularly focusing on the advantageous position of political power in the resource allocation process (Bian and Logan 1996; Lin 1995; Parish and Michelson 1996; Rona-Tas 1994; Walder 1995a). The market transition theory continues to evolve, addressing criticisms by highlighting that market reforms are characterized by locality, relativity, and path dependence (Cao and Nee 2000; Nee 1991; Nee and Matthews 1996; Nee and Cao 1999). Despite the ongoing role of redistributive power, empirical studies support the increasing influence of education on income returns since the market transition, which complicates the process of status attainment under the national socialist system. The market transition theory and various competitive perspectives predominantly consider income return as the variable of interest, bypassing direct class analysis. However, at their core, these theories essentially address whether the opportunity to become elite after marketization leans towards individuals with higher human capital or continues to necessitate political capital as a prerequisite for reaching elite status (Bian 2002). Research on the status attainment of socialist elites provides a direct response to this question. Studies by Szelenyi and Martin (1988) on the socialist transformation in Eastern European countries propose that due to the weak economic foundation of socialist regimes, these regimes should place significant emphasis on professional skills and advanced management experience for the rational needs of economic development and military competition. This provides a structural position for intellectuals to become a new class—technical bureaucrats. Walder suggests that socialist elites comprise two types: those who are politically loyal but lack strong professional skills, and those who are not politically loyal but possess professional skills. Accordingly, there are two distinct upward mobility career paths in socialist countries, leading to different elite positions through selective political review and acceptance. For those preparing for a political career, superiors primarily assess them based on their education and political loyalty, prioritizing their admission to the party. Conversely, for those preparing for a professional career, selection is based on their education, with political loyalty not being the main criterion for promotion, and superiors do not prioritize their admission to the party (Walder 1995b). Numerous empirical studies have found that with the deepening of market transformation, this dual-path model for elite status attainment has not significantly changed. Party members, especially those who join the party early in their careers, enjoy advantages in promotion and resource allocation (Bian, Shu, and Logan 2001; Zang 2001). This leads most stratification scholars to believe that political inequality based on party membership forms the core of the stratification order in socialist countries (Li and Walder 2001). On the other hand, education, especially university education, significantly impacts both career paths of management elites and professional elites (Walder, Li, and Treiman 2000). Subsequent studies have refined the types of socialist elites, such as government system elites and party system elites (Zang 2001), system insiders and system outsiders (market elites) (Lv and Fan 2016 ), thus enriching the dual-path model. Zhou argues that the dual-path model emphasizes a stable institutional foundation, which results in the continued existence of two segmented career development paths in the Chinese bureaucratic system. However, Zhou underscores the influence of macro political processes on bureaucratic career patterns more. Macro political processes encompass two aspects: changes in state policies affect bureaucratic career patterns by altering selection criteria for official recruitment and promotion, and the inherent tension between centralized states and bureaucratic interests leads to frequent bureaucratic system reforms and political movements, disrupting career patterns. Significant changes in political opportunities across different historical periods have resulted in major differences in life opportunities for labor employment among different age groups (Zhou 2015 ). In previous studies examining the influence of human capital and political capital on the process of status attainment, two points are particularly worth discussing. First, income is often used as the core explanatory variable, with less focus on occupational status research. Elite research tends to dominate occupational status studies, leaving general social status attainment relatively underexplored. This is largely because many scholars believe that under the planned economic system, China did not have a real labor market. Labor was considered a national resource, centrally allocated and controlled by the state. There was no free movement of labor, and unemployment was not a concern. The labor market only began to form and align with the characteristics of a market-oriented society after the reform and opening up (Huang 2008 ). The system transformation subsequently strengthened the significance of occupational status (Bian, Li, and Li et al. 2006 ). The absence of a labor market does not mean that there was no occupational differentiation in socialist society. This study argues that the previous research viewpoint on elite status attainment—that China's occupational mobility mechanism is a unique mixture of loyalty to the political system and the meritocratic principles of modern occupational mobility (Li and Walder 2001)—also applies to the attainment of non-elite status. During the transition from a redistributive system to a market-oriented system, the roles and mechanisms of human capital and political capital varied across different historical stages due to differences in macro political processes. Second, in terms of research design, previous studies typically divided the history of New China into different stages based on major historical events and compared the status attainment patterns across these stages. In early empirical studies, scholars often used the Cultural Revolution (1966) as a benchmark for dividing historical periods when analyzing the differences in status attainment between the socialist system and the Cultural Revolution period (Parish 1984; Whyte and Parish 1984). When studying status attainment since the market transition, the reform and opening up is usually used as the dividing line, often splitting the period into before 1979 and after 1979 (Li 2003 ). Zhou et al. (1996) in dynamic stratification model studies divided the history of New China into three stages: 1949–1965, 1966–1979, and 1980–1994. With the availability of more survey data, later scholars further subdivided the period since the reform and opening up. For instance, Wu ( 2006 ) and Wu ( 2010 ) used 1986 as a dividing line, splitting the period into 1978–1986 and 1987–1996. Some scholars used 1992 (Deng Xiaoping's Southern Tour Speech) and 2002 (the convening of the Sixteenth Party Congress) as dividing lines, categorizing the reform and opening up into the early stage, deepening stage, and comprehensive deepening stage. As Lv and Fan ( 2016 ) divided the status attainment of urban and rural elites in China into three historical stages: 1978–1992, 1993–2002, and 2003–2010. By comparing the status attainment patterns across different historical stages using historical periodization, this approach can generally reflect the differences in status attainment of the Chinese population over time. It can also illustrate the impact of major historical events or national policies on people's life trajectories, as well as compare the relative importance of human capital and political capital at different times. However, this discontinuous division implies a homogeneity assumption of status attainment patterns within different stages (Fang and Feng 2018 ). That is, it assumes that the effect of the independent variable on the dependent variable remains constant within the same historical stage, which may not be an ideal research design method 3 . This study attempts to analyze the role and trend of human capital and political capital in occupational status attainment by constructing a sample database with specific year information, rather than dividing historical stages. 3. Research Design (1) Measurement Dependent Variable The dependent variable in this study is occupational status, measured using the International Socio-Economic Index (ISEI) of occupational status for individuals' current or last job. This is a continuous variable ranging from 16 to 90. Independent Variables The core variables of this study are human capital and political capital, measured by education level and party membership, respectively. Education is measured in two ways: Years of Education: Based on individuals' educational background. University Education: Categorizes individuals based on their highest degree to determine if they have received an university education (1 for yes and o for no), thus observing the role of a college degree in occupational status attainment. Party membership is measured based on people's political identity, where party members are coded as 1 (including a small number of members from democratic parties), and non-party members are coded as 0. Control Variables Gender: Male is coded as 1, female as 0. Current Household Registration: Urban household registration is coded as 1, agricultural household registration as 0. Father's Education Level: Measured based on the father's education level when the respondent was aged 14 (or 18), converted to years of education using the same conversion method as above. Father's Occupational Status: Measured based on the International Socio-Economic Index (ISEI) for the respondent's father when the respondent was aged 14 (or 18). Entry Time: Measured based on the year the respondent first started working. (2) Data Source This study merged the urban samples from all 10 waves of the China General Social Survey (CGSS) conducted in 2003, 2005, 2006, 2008, 2010, 2011, 2012, 2013, 2015, and 2017 4 , resulting in a total sample size of 49,403 individuals. The study controlled for the age of respondents between 18 and 65 years old (at the time of the survey) and excluded samples without work experience, resulting in an effective analytical sample of 43,235 individuals. Descriptive statistics for each variable in different survey years are shown in Table 1 . Table 1 Descriptive Statistics of Urban Samples in China General Social Survey CGSS 2003–2017 (N = 43,235) discrete variables CGSS2003 (4049) CGSS2005 (4431) CGSS2006 (4639) CGSS2008 (3164) CGSS2010 (5272) CGSS2011 (2310) CGSS2012 (5148) CGSS2013 (4957) CGSS2015 (3965) CGSS2017 (5300) Gender Female Male 48.8 51.2 52.2 47.8 53.6 46.4 52.0 48.0 51.6 48.4 53.6 46.4 48.6 51.4 48.7 51.3 52.6 47.4 53.3 46.7 Hukou Agricultural non-agricultural 5.8 94.2 9.4 90.6 18.2 81.8 20.3 79.7 26.4 73.6 30.9 69.1 30.1 69.9 33.9 66.1 35.1 64.9 37.2 62.8 University Educational No yes 78.5 21.5 81.6 18.4 81.9 18.1 78.2 21.8 74.1 25.9 75.8 24.2 73.4 26.6 73.9 26.1 73.4 26.6 68.8 31.2 Party membership Non-Party Members Party members 79.7 20.3 87.1 12.9 89.5 10.5 86.2 13.8 84.3 15.7 86.5 13.5 85.3 14.7 87.4 12.6 87.5 12.5 87.0 13.0 continuous variables CGSS2003 CGSS2005 CGSS2006 CGSS2008 CGSS2010 CGSS2011 CGSS2012 CGSS2013 CGSS2015 CGSS2017 ISEI [16, 90] 41.7(16.6) 42.3(15.2) 42.3(13.8) 41.9(17.4) 40.3(15.7) 40.3(16.6) 40.6(15.7) 39.8(15.7) 39.9(16.9) 42.2(15.4) Age [18, 65] 42.6(11.2) 41.3(11.6) 41.4(12.0) 40.6(12.1) 42.7(12.0) 43.0(12.1) 43.2(12.1) 43.2(12.3) 43.6(12.5) 44.3(12.7) Years of education [0, 20] 10.8(3.2) 10.4(3.5) 10.5(3.3) 10.6(3.5) 10.7(3.9) 10.6(3.6) 10.8(3.8) 10.7(3.8) 10.7(4.1) 11.0(4.2) Years of father's education [0, 20] 6.1(4.7) 6.2(4.6) 6.4(4.3) 6.3(4.5) 6.2(4.6) 6.3(4.5) ) 6.3(4.5) 6.2(4.5) 6.0(4.6) 6.2(4.7) the ISEI of father [16, 90] 34.6(19.0) 32.5(18.2) 35.7(15.7) 34.3(20.1) 35.4(15.6) 35.5(16.5) 35.4(16.2) 33.9(15.3) 30.7(18.7) 34.8(16.3) (Note: Discrete variables are percentages in the cells, and continuous variables are means (standard deviations) in the cells.) (3) Analysis Model This study divided the respondents into different groups based on their year of entry (1944–2017). Due to the limited number of samples entering before 1950, these samples were grouped into the year 1950. A total of 68 entry year cohorts from 1950 to 2017 were obtained. A mixed effects model was then used to analyze the impact of factors such as human capital and political capital on occupational status. Unlike previous studies that divided years into different birth cohorts or major event periods, this study used specific years as stratification variables, which provides more detail and eliminates concerns about the accuracy of group division. Using time as a stratification variable is an important means of analyzing repeated survey data, known as "pseudo-panel data," where each sample appears only once in the survey. This approach avoids the autocorrelation issues associated with repeated sample surveys (longitudinal data) or time series data, and can reflect the changing trend of sample means over time. Depending on the different measurement methods of the dependent variable, A mixed OLS model is used. The statistical model was divided into two levels: Level 1. is an individual-level model: $${ISEI}_{ij}=\beta \text{0}\text{j}+\beta \text{1}\text{j}\text{*}\text{g}\text{e}\text{n}\text{d}\text{e}\text{r}+\beta \text{2}\text{j}\text{*}\text{h}\text{u}\text{k}\text{o}\text{u}+\beta \text{3}\text{j}\text{*}\text{e}\text{d}\text{u}+\beta \text{4}\text{j}\text{*}\text{p}\text{a}\text{r}\text{t}\text{y}+\beta \text{5}\text{j}\text{*}\text{e}\text{d}\text{u}\_\text{f}+\beta \text{6}\text{*}\text{i}\text{s}\text{e}\text{i}\_\text{f}$$ Level 2. is a random year effect model: \({\beta _{kj}}={\gamma _{k0}}+{\mu _{kj}}\) , [k = 0, 3, 4] In these models, i represents the individual, j represents the year of entry, and k correspond to the intercepts and the coefficients of the independent variables. This study focuses on the impact of education and party membership variables on status attainment and trends over time. For simplicity, the random effects of gender, birthplace, father's education level, and occupational status variables are fixed at 0. All continuous variables in the analysis model are centered based on the year of entry (i.e., centered around the group average). 4. Data Analysis (1) Mixed Effects Model Construction To analyze the factors influencing occupational status, this study employs a mixed effects model using the respondent's current or last occupation's Index of Socioeconomic Status (ISEI) as the dependent variable. The year of initial job entry is used as a stratification variable. The models are constructed as follows: Model 1: Null Model This model includes only the intercept term and random effects of the intercept. The intercept represents the average occupational status of the total sample, while the random effects capture the variation in occupational status for samples entering in different years. Model 2: Fixed Effects Model This model adds explanatory and control variables. Except for the intercept, the effects of each variable are fixed, making this model similar to a regular regression model that does not account for year differences. Model 3: Random Effects Model Building on Model 2, this model allows for intergroup differences in the impact of education level and party membership variables on individuals' occupational status. Model 4: University Education Impact Model In this model, the education level variable in Model 3 is replaced with a dummy variable indicating whether the individual has received university education. This model focuses on the impact of university education on individuals' occupational status and its changing trends. The estimation results for these models are shown in Table 2 . Table 2 Mixed Effects Analysis of the Factors Influencing ISEI (n = 43,235, N = 68) fixed effects Model 1 Model 2 model 3 model 4 Intercept 40.16*** (0.841) 37.28*** (0.861) 37.29*** (0.883) 32.33*** (0.564) Sex (female = 0) -0.969*** (0.128) -0.989*** (0.128) -0.409** (0.128) Hukou (agricultural = 0) 3.346*** (0.163) 3.354*** (0.163) 5.323*** (0.159) Years of education 1.865*** (0.024) 1.879*** (0.040) college (no = 0) 13.550*** (0.383) Party (no = 0) 6.594*** (0.195) 6.301*** (0.395) 6.690*** (0.504) years of education of father 0.111*** (0.018) 0.109*** (0.018) 0.202*** (0.018) the occupational status (ISEI) of father 0.047*** (0.004) 0.047*** (0.004) 0.0602*** (0.004) random effects variance components variance components variance components variance components Intercept 46.718*** 48.208*** 50.763*** 19.492*** Years of education .056*** college 5.819*** Party 6.690*** 12.581*** residuals 233.428*** 169.883*** 168.823*** 172.039*** AIC 358759.2 345077 344960.9 345750.9 BIC 358785.2 345155 345056.3 345846.3 Log likelihood -179376.6 -172529.5 -172469.4 -172864.5 (2) Changes in the Trend of Occupational Status Attainment with Entry Time By comparing the random effects of intercept terms in Models 1–4, significant differences in intercept terms across different years of entry were observed. Taking Model 3 as an example, the intercept term represents the occupational status of non-party female agricultural hukou holders with average education levels and family background (father's education and occupational status). To illustrate the trend of their average occupational status over time, this study calculated the mixed effects of the intercept and plotted Fig. 1 . From Fig. 1 , it can be seen that the average occupational status of individuals shows an overall increasing trend year by year: First, Early Days of the Founding of the Country (1949–1956): During the period of socialist revolution, the national economic strategy was guided by the "one transformation, three reforms" general line, which thoroughly transformed individual industrial and commercial enterprises and capitalist industrial and commercial enterprises (the destratification social experiment) (Parish 1984). This established a state socialist redistributive economic system based entirely on public ownership, essentially eliminating the private economy and making the class structure more uniform. During this stage, the average occupational status of people showed a declining trend. Second, Post-Socialist Transformation Period: After the completion of socialist transformation, China entered a period of rapid development. Despite the impacts of the Great Leap Forward and major natural disasters, the average occupational status of people continued to increase significantly. Third, Cultural Revolution (1966–1976): The occurrence of the Cultural Revolution led to a large number of educated youths being sent to the countryside, resulting in a significant decline in people's occupational status. This trend continued until after the end of the Cultural Revolution in 1976. Forth, Reform and Opening Up (Post-1978): Following the reform and opening up in 1978, China transitioned from a redistributive economy to a market economy, with the degree of marketization continuously increasing. Consequently, people's average occupational status continued to rise. The analysis of the average trend of people's occupational status indicates that in a relatively stable political environment, with the development of the national economy and the improvement of industrialization levels, people's average occupational status will continue to rise. However, during sensitive periods, people's average occupational status is susceptible to macro-political interference. (3) Trends in the Time Changes of Occupational Status Attainment Influenced by Educational Level Changes in the Effects of Years of Education The impact of education level (fixed effect) is consistent with previous studies, showing that education level has a significant positive effect on improving people's occupational status. For every additional year of education, the average increase in occupational status is around 1.879 points. However, the effect of education level varies significantly between different entry years, as indicated by the significant variance components. Figure 2 illustrates the impact and changing trends of education years on people's occupational status. Analysis reveals that the influence of education level on occupational status shows multiple fluctuations: First, Early Days of the Country's Founding: During the transitional period, the general line led to the transformation of individual industrial and commercial economies and capitalist industrial and commercial economies. Individuals with higher education levels, such as individual business owners and private entrepreneurs, largely disappeared and joined the ranks of the working class, resulting in downward mobility from an occupational stratification perspective. Second, Post-Transformation Industrial Development: After the completion of the socialist transformation, China entered a period of industrial development, despite encountering major historical events such as the Great Leap Forward and natural disasters. The effects of industrial development became apparent, and the influence of education level on occupational status gradually strengthened, initially reflecting the positive role of education in an industrial society. Third, Cultural Revolution: During the Cultural Revolution, economic development stagnated, and the influence of education on occupational status gradually declined. This trend continued until the end of the Cultural Revolution. Forth, Reform and Opening Up: The beginning of reform and opening up alleviated the decline in the influence of education on occupational status. The role of education level in influencing occupations strengthened, aligning with the expectations of market transformation theory. Fifth, Popularization of Nine-Year Compulsory Education (1992): With the popularization of nine-year compulsory education, the education level of the labor force entering the market significantly improved, leading to a brief slight decline in the role of education. This trend continued until around 2000 when the role of education level rose again. Last, Higher Education Expansion (1999): Due to the large-scale expansion of higher education enrollment in 1999, the number of college students surged, leading to a decline in the advantage of education level around 2005. This decline almost continued until the end of the research data year. Despite the multiple fluctuations in the role of education level in occupational status attainment, the positive effect of education on status attainment remained consistent (there was no year when the educational effect was negative). The market transformation theory explains the impact of education on status attainment in the early stages of reform and opening up, but this process is also regulated by other national policy processes. Changes in the Role of Higher Education Model 4 specifically analyzed the impact of university education on people's occupational status. The results indicated that individuals who had received university education had an average occupational status that was 13.550 points higher compared to those with a high school education or below. To understand the role of higher education in occupational status attainment, it is essential to consider the development of higher education in New China. According to national statistical data 5 : In 1949, at the establishment of New China, the proportion of university students in the total population was only 2.2 per 10,000 people. By 1978, after the resumption of the college entrance examination, this proportion had increased to 8.9 per 10,000 people. By 1998, it had further increased to 51.9 per 10,000 people. Following the expansion of university enrollment in 1999, the scale of university students continued to increase, reaching 257.6 per 10,000 people by 2017—five times the scale before the expansion. University education has gradually shifted from elite education to mass education. As a result, university students face increasing competition in the labor market, prompting many to pursue graduate studies to alleviate employment pressure and enhance their human capital, thereby maintaining an advantage in the labor market. Figure 3 illustrates the impact of university education on occupational status and its changing trends over time. Key observations include: First, Before the Resumption of the College Entrance Examination: The proportion of university students in China was very low. Among samples entering the workforce from 1950 to 1955, no university students were selected, so only the average value trend line is shown in the figure. Before 1965, the number of university student samples was also less than 10, possibly leading to statistical bias. Therefore, the trend reflected in the figure before 1965 may not be accurate. Second, Early Stages of the Cultural Revolution: Due to the policies targeting intellectuals and the movement of educated youth going to the countryside, the impact of university education on occupational status experienced a rapid decline. This is consistent with the findings of Zhou et al. (2015) on the stratified dynamic process theory. However, this trend began to reverse in the later stages of the Cultural Revolution as the scale of educated youth going to the countryside decreased, and some policies relaxed, allowing early educated youth to return to cities. Third, Post-Cultural Revolution and Reform Period: After the resumption of the college entrance examination in 1977, the scale of university education in China increased. However, as China had not yet formed a labor market, the employment of university graduates still followed the "allocation" model, and university education did not receive the expected status returns from market transformation theory. The relative importance of university education to occupational status decreased, contrary to the expectations of market transformation theory. Forth, Post-2000 Trends: The overall return of university education to occupational status continued to decline, but the rate of decline slowed compared to earlier years. In 1996, the country gradually abolished the allocation system for graduates, allowing for a two-way selection between graduates and employers, theoretically increasing the role of higher education in status attainment. However, the rapid increase in the supply of talent due to higher education expansion led to increased employment difficulties for college students, further devaluing university degrees. To counter this, many university graduates pursued postgraduate studies. Post-2010, the occupational status and returns of university graduates increased again, mainly due to a significant proportion of postgraduates in the sample. Figures 2 and 3 together indicate that while the impact of education level on occupational status has a positive effect, its effectiveness has fluctuated under different socio-economic systems and market transformations. Before the reform and opening up, especially during the Cultural Revolution, the relative effect of education level declined. Since the reform, although the role of education level in status attainment has strengthened, the increased supply of highly educated talents has led to signs of degree devaluation rather than sustained enhancement. (4) The Time Trend of the Influence of Party Membership on the Attainment of Occupational Status Party membership has a significant impact on people's current (or last) occupational status. Compared to non-party members, the average occupational status of party members is about 6.3–6.7 points higher (p < 0.01, see Models 2 to 4). However, the role of party membership also varies significantly over different periods. As depicted in Fig. 4 , the influence of party membership on occupational status shows a trend similar to that of higher education, given that opportunities for higher education and party membership often intertwine 6 . First, From the Founding of the Country to the Cultural Revolution: During this period, the role of party membership in people's occupational status continued to strengthen, reflecting the significant advantage of party members in resource allocation under the redistributive system. Second, Cultural Revolution: During the Cultural Revolution, the role of party membership experienced a V-shaped trend of decline followed by an increase. Third, Post-Reform and Opening Up (1978 onwards): After the reform and opening up, the importance of party membership declined again. Over the past decade or so since 2000, the effect of party membership has fluctuated slightly below the average effect. This is consistent with the expectations of market transition theory, as the role of political capital begins to relatively decline after experiencing market-oriented reforms. Forth, Post-2000 Trends: Under the influence of higher education expansion, to alleviate employment difficulties and comply with the needs of state organizations, the number of university graduates participating in civil service examinations, "three supports and one assistance," and other programs has increased. In the selection for these organizations, political qualities are continuously emphasized as an important criterion. After 2010, the occupational status returns for party members began to rise again, and from the slope perspective, the upward trend is very steep. 5. Conclusion and Discussion (1) Overview The dynamic process of social status attainment, as a key aspect of social stratification, underscores the elasticity of social structure. The classic status attainment model, rooted in the development of industrial society, suggests that the constraints of ascriptive factors on an individual's socioeconomic status will diminish over time, while the influence of achievement factors will grow, indicating a move towards a more open social structure and a decrease in social inequality levels. However, the trajectory of New China's industrial development, marked by significant political events and policy shifts, diverges from traditional industrialization logic. After embracing market-oriented reforms, transitioning from a state socialist redistribution system to a market economy introduced notable shifts in the mechanisms of social stratification across different historical stages. (2) Theoretical Implications Solely applying the industrialization logic to analyze the changes in Chinese people's status attainment mechanisms—by examining family background and human capital factors—may not yield theoretical breakthroughs. For countries undergoing socialist transition, the interplay between redistribution logic, marketization logic, and the sustained advantage of political power in resource allocation garners significant theoretical interest. Market transformation theory posits that with marketization advancement, the advantage of redistributive power should gradually cede to market forces. However, empirical evidence challenges this notion, revealing that political power retains a continuous advantage in income returns and elite status attainment during the socialist transformation. Human capital's role is also on the rise, creating a dual pathway alongside political capital for forming socialist elites. (3) Empirical Findings This study leverages data from the China General Social Survey (CGSS) spanning 2003 to 2017 to examine the impact and trends of education level and party membership on individuals' occupational status. Findings indicate a steady increase in the average occupational status of Chinese people and their opportunities to ascend to elite positions, albeit with occasional declines. (4) Key observations include : Education Level: Positively impacts average occupational status, though its influence significantly fluctuates across different historical periods. Early market transformation stages saw a notable increase in education's role in status attainment, which later declined with higher marketization levels, expansion of higher education, and policy changes, contradicting market transformation expectations. Party Membership: The role of party membership has experienced significant shifts over time. Initially, its advantages in attaining professional status diminished but have seen a resurgence in recent years, particularly as political qualities gain prominence in selection processes for political organizations. (5) Reflections and Directions for Future Research The study's findings highlight the nuanced and heterogenous effects of human capital and political capital across different periods, suggesting that macro factors not yet observed may influence or constrain status attainment processes. The observed V-shaped changes in the influence of university education and party membership during the Cultural Revolution underscore the complexity of status attainment mechanisms during different historical phases. This complexity suggests that simplifying China's social stratification mechanisms based solely on major events may overlook critical nuances, emphasizing the need for detailed examination under appropriate conditions. In summary, while historical events provide a general framework for understanding social change in China, they may not fully capture the intricate dynamics of social stratification mechanisms. Future research should continue to explore these complexities, considering the multifaceted interactions between human capital, political capital, and broader socio-political contexts. Declarations Data availability statement Publicly available datasets were analyzed in this study. This data can be found here: http://www.cnsda.org/index.php?r=projects/index. Ethics statement Ethical review and approval were not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study. Funding This study was supported by the National Social Science Foundation of China project "Research on the Constraints and Mechanisms of Health Equality in the Context of the Healthy China Strategy (Grant no.21BSH008)." Acknowledgements The authors would like to thank the Social Survey Center of Renmin University of China for providing data for the research, and to all the project team participants and interviewees. Contributions Xxx was responsible for the framework and idea of the entire text, data processing and analysis, and wrote the initial draft of this study. The author takes full responsibility for this manuscript. References Bian Yanjie. 2002. Market Transformation and Social Stratification: American Sociologists Analyze China (Chinese). Beijing: Sanlian Bookstore. Bian, Yanjie., Li, Lulu., Li, Yu., et al., 2006, Structural Barriers, Institutional Transformation and Status Resource Content, Chinese Social Sciences(Chinese) . 5:100-109. Bian, Yanjie and John R. Logan. 1996. "Market Transition and the Persistence of Power: The Changing Stratification System in Urban China." American Sociological Review 61(5):739-758. Bian, Yanjie, Xiaoling Shu and John R. Logan. 2001. "Communist Party Membership and Regime Dynamics in China." Social Forces 79(3):805-841. Blau, Peter M. and Otis Dudley Duncan. 1967. The American Occupational Structure . New York: the free press. Cao, Yang and Victor G. Nee. 2000. "Comment: Controversies and Evidence in the Market Transition Debate." The American Journal of Sociology 105(4):1175-1189. Erikson, Robert and John H. Goldthorpe. 1992. The Constant Flux: A Study of Class Mobility in Industrial Societies . Oxford: Oxford University Press. Fang, Changchun and Feng, Xiaotian. 2018. Social origin and education attainment - historical investigation based on CGSS data of 70 age groups. Sociological Research (Chinese) . No. 2:140-163. Featherman, D.L, F.L. Jones and R.M Hauser. 1975. "Assumptions of Social Mobility Research in the United States: The Case of Occupational Status." Social Science Research 4:339-360. Grusky, David B. 2005. Social Stratification: Class, Race, and Gender in Sociological Perspective Boulder: Westview Press. Huang, Xianbi. 2008. Institutional spatial analysis of the operation of the emerging labor market and job-seeking channels. in Institutional Transformation and Social Stratification: Based on the 2003 China General Social Survey (Chinese) . Beijing: Renmin University of China Press. Li, Bobai and Andrew G. Walder. 2001. "Career Advancement as Party Patronage: Sponsored Mobility into the Chinese Administrative Elite, 1949-1996." The American Journal of Sociology 106(5):1371-1408. Li, Chunling. 2005. Fracture and Fragmentation: An Empirical Analysis of Social Stratification in Contemporary China (Chinese) . Beijing: Social Science Literature Publishing House. Li, Lulu. 2003. Institutional Transformation and the Changing Mechanisms of Stratification: From "Indirect Reproduction" to the Coexistence of "Indirect and Direct Reproduction". Sociological Research (Chinese). No. 5:42-51. Li, Lulu., Shi, Lei and Zhu, Bin.2018. Solidification or Mobility? --Forty Years of Class Structure Change in Contemporary China. Sociological Research (Chinese) . 6:1-34. Lin, Nan. 1995. "Local Market Socialism: Local Corporation in Action in Rural China." Theory and Society 24(3):301-354. Liu, Xin. 2003. Market transformation and social stratification: the focus of theoretical debates and issues to be studied. Chinese Social Sciences (Chinese) . 5:102-110. Lv, Peng and Fan, Xiaoguang. 2016. The two-track path of intergenerational reproduction of elite status in China (1978-2010). Sociological Research (Chinese) . 5:114-138. Nee, Victor. 1989. "A Theory of Market Transition: From Redistribution to Markets in State Socialism." American Sociological Review 54(5):663-681. Nee, Victor. 1991. "Social Inequalities in Reforming State Socialism: Between Redistribution and Markets in China." American Sociological Review 56(3):267-282. Nee, Victor and Rebecca Matthews. 1996. "Market Transition and Societal Transformation in Reforming State Socialism." Annual Review of Sociology 22:401-435. Nee, Victor and Yang Cao. 1999. "Path Dependent Societal Transformation: Stratification in Hybrid Mixed Economies." Theory and Society 28(6):799-834. Parish, William L. 1984. "Destratification in Chinese Society." Pp. 84-120 in Class and Social Stratification in Post-Revolution China , edited by J. L. Watson. Cambridge: Cambridge University Press. Parish, William L. and Ethan Michelson. 1996. "Politics and Markets: Dual Transformations." The American Journal of Sociology 101(4):1042-1059. Rona-Tas, Akos. 1994. "The First Shall Be Last? Entrepreneurship and Communist Cadres in the Transition from Socialism." American Journal of Sociology 100(1):40-69. Szelenyi, Ivan and Bill Martin. 1988. "The Three Waves of New Class Theories." Theory and Society 17(5):645-667. Walder, Andrew G. 1995a. "Local Governments as Industrial Firms: An Organizational Analysis of China's Transitional Economy." The American Journal of Sociology 101(2):263-301. Walder, Andrew G. 1995b. "Career Mobility and the Communist Political Order." American Sociological Review 60(3):309-328. Walder, Andrew G., Bobai Li and Donald J. Treiman. 2000. "Politics and Life Chances in a State Socialist Regime: Dual Career Paths into the Urban Chinese Elite, 1949 to 1996." American Sociological Review 65(2):191-209. Wang, Chunguang. Zhao Yufeng. and Wang Yuqi. 2018. New trends in the social stratification of peasants in contemporary China. Sociological Research (Chinese) . 1:63-88. Wu, Xiaogang. 2006. "Going to the Sea": Self-employment Activities and Social Stratification in the Transformation of China's Urban and Rural Labor Markets (1978-1996). Sociological Research (Chinese) . 6:124-150. Wu, Yuxiao. 2010. Family Background, Institutional Transformation and Intergenerational Transmission of Chinese Rural Elites (1978-1996). Sociological Research (Chinese) . 2:125-150. Xie, Guihua. 2014. Study on the Attainment of Socio-Economic Status after "Agricultural Conversion to Non-Formal". Sociological Research (Chinese) . 1:40-56. Xu, Xinxin. 2000. Social Structural Change and Mobility in Contemporary China (Chinese) . Beijing: Social Science Literature Press. Whyte, Martin King and William L. Parish. 1984. Urban Life in Contemporary China . Chicago: University of Chicago Press. Zang, Xiaowei. 2001. "University Education, Party Seniority, and Elite Recruitment in China." Social Science Research 30:62-75. Zhou, Xueguang, Nancy Brandon Tuma and Phyllis Moen. 1996. "Stratification Dynamics under State Socialism: The Case of Urban China, 1949–1993." Social Forces 74(3):759-796. Zhou, Xueguang. 2015, State and life chances: redistribution and stratification in urban China 1949-1994(Chinese) . Beijing: Renmin University of China Press. Zhou, Yi. 2009, After the Blau-Duncan model: transformation or challenge, Sociological Research (Chinese) . 6:206-225. Footnotes This study uses data from the "China General Social Survey (CGSS)" project hosted by the China Survey and Data Center of Renmin University of China. The authors thank this institution and its staff for providing data assistance, and take full responsibility for the content. In the research on the attainment of general social status in China, researchers not only focus on the impact of variables such as family background and education on people's social status attainment, but also pay attention to the role of intermediate mechanisms such as family cultural capital, social networks (capital), and political capital. In terms of outcome variables, in addition to focusing on occupational status, attention is also paid to education level, income status, party membership opportunities, unit type, and level, among others. There is a lot of literature on this topic, not listed one by one. Zhou ( 2015 ) pointed out that when analyzing the impact of dynamic processes on people's life opportunities, the ideal research design is to use a prospective research design to track a representative individual sample. However, due to historical or political reasons, this research design cannot be implemented. An alternative approach is to collect people's life event history information at different stages through a retrospective design (the method used by Zhou et al.), or to use time-repeated samples to measure the changes and persistence of individual life opportunities over time (as used in this study). The data and sampling design for all waves of the China General Social Survey (CGSS) can be obtained through the China Social Survey and Data Center at Renmin University of China ( http://nsrc.ruc.edu.cn/ ) and the National Survey Data Archive website ( http://cnsda.ruc.edu.cn/ ) Data source: "Statistical Data Compilation of Fifty Years of New China (1949–1999)" and other corresponding yearbooks. The Pearson correlation coefficient of the mixed effects of the two reached 0.696. Additional Declarations (Not answered) Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4591449","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":417770071,"identity":"fbfdfebb-cf9f-44fc-b297-6e573d490f78","order_by":0,"name":"Fuqin Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIie3QPQrCMBTA8ZRCu6R27WK9QiCDSC/zgoNLce7QISB0dVUQ9QhOzk8Kdam4OuoJDLiKGAVxq3ETzH9K4P3IByE22w/m+SNEyJ5rQELcz6RFK4GqZl+QOEr5Zlqw196AeARYGcyvcTdcnpBkiZD+Dj8QhDJYM96bHPXF6oGQdAjNxJH4IGJ1QECnKIWMKGsmriPLYPYiNxPiuWQzlZrspSbShFD9GlVxzg76k6Ea8IKmzaSzOF8U5HHM9nVfqTxpj/26mbyLUiDwONdwXhdu0XzYZrPZ/qo7MoVN4sF6lXoAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0009-2256-7474","institution":"Tongji University","correspondingAuthor":true,"prefix":"","firstName":"Fuqin","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-06-17 03:05:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4591449/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4591449/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":77022047,"identity":"e7055655-2a2c-47f2-924d-7ffbc751bfe9","added_by":"auto","created_at":"2025-02-24 11:01:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":50663,"visible":true,"origin":"","legend":"\u003cp\u003eThe Changing Trend of Average Occupational Status with People's Entry Time\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4591449/v1/b30979532f27a5733a232729.png"},{"id":77022048,"identity":"b736c214-12a8-4a95-9308-845a4fc92dcc","added_by":"auto","created_at":"2025-02-24 11:01:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":58906,"visible":true,"origin":"","legend":"\u003cp\u003eThe Impact of Education Level on ISEI and Changing Trends\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4591449/v1/74f3a784dcc697b17847fa01.png"},{"id":77024494,"identity":"9168233e-b388-4c54-8bc2-8e61061c08ea","added_by":"auto","created_at":"2025-02-24 11:09:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54869,"visible":true,"origin":"","legend":"\u003cp\u003eThe Impact of University Education on ISEI and Its Changing Trends\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4591449/v1/f6d2cbf04211a6f343953ebc.png"},{"id":77024495,"identity":"d3522eb3-d6d0-4684-b960-129c0a8e2411","added_by":"auto","created_at":"2025-02-24 11:09:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":54412,"visible":true,"origin":"","legend":"\u003cp\u003eThe Impact of Party Membership on ISEI and Changing Trends\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4591449/v1/99bc8a7266bf004d8da3ca52.png"},{"id":77024952,"identity":"b711b62d-c5a3-406f-970d-61ea379fe37e","added_by":"auto","created_at":"2025-02-24 11:17:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1344313,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4591449/v1/402ac92b-1f5c-41e6-829a-2e826b79b4c8.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Education, Party Membership, and Occupational Status Attainment in China's Social Transformation (1950-2017)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSince the founding of New China, especially since the reform and opening up, there have been significant changes in the social class structure and intergenerational mobility in China. These changes have attracted substantial attention from both domestic and foreign scholars. The study of social stratification and mobility has thus become one of the most active areas in sociological research. Previous studies have primarily focused on the dynamic changes in the stratification structure, paying less attention to the dynamic changes in mobility opportunities, particularly at the micro level of status attainment processes (Li, Shi and Zhu 2018).\u003c/p\u003e \u003cp\u003eThe classic status attainment model, known as the Blau and Duncan model, summarizes the mechanism of status attainment as a combination of ascriptive factors (such as parental background) and achievement factors (such as education). It emphasizes that in industrialized societies, the influence of ascriptive factors will gradually decrease, while the role of achievement factors will become the dominant mechanism in a market-oriented society (Blau and Duncan 1967). This logic has been extensively tested in studies of market-oriented countries and has become the foundational model for analyzing social mobility processes both domestically and internationally. However, unlike Western developed industrial societies, the industrialization process in new China is accompanied by the transformation of social systems and distribution rules\u0026mdash;from a planned economy system with redistribution rules to a market-oriented system with performance-based distribution. This transformation is achieved under the unified leadership of the Communist Party of China, making China's occupational mobility mechanism a unique mixture of political loyalty and the meritocratic principles of modern occupational mobility. This complexity has led to the market transition theory (Nee 1989) being questioned by many scholars from its inception (Liu \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch on market-oriented countries suggests that political inequality based on party membership is central to the hierarchical order in socialist countries. The redistribution of power represented by party membership continues to play a significant role in people's status attainment, especially in the occupational and income status of the bureaucratic class, without showing a downward trend (Bian and Logan 1996; Lin 1995; Parish and Michelson 1996; Rona-Tas 1994; Walder 1995a). In competitive explanations of political capital and human capital, Walder's dual-path theory on the status attainment of Chinese elites is particularly noteworthy. This theory posits that political loyalty (measured by party membership) is the primary condition for becoming an administrative elite, while education is crucial for becoming a professional elite (Walder 1995b). Even after market-oriented reforms, due to the rational need for political stability and economic development, the influence of higher education on becoming administrative and professional elites has significantly increased. However, this dual elite status attainment pattern has not changed significantly, with party members continuing to have advantages in position promotion and resource allocation (Li and Walder 2001). The hierarchical dynamic process model proposed by Zhou et al. (1996) suggests that macro political processes and changes in state policies affect people's life opportunities (education, occupational activities, work organization, career transitions, promotions, income, and housing) and fluctuate over time. The returns on human capital and political capital differ in the redistribution logic of the socialist state system and the performance distribution logic since market-oriented reforms, impacting people's life opportunities differently. The hierarchical dynamic model provides a new analytical perspective for studying changes in the social class structure in transitional China. However, testing the impact of macro political processes or changes in state policies on the stratification mechanism (reflected through period effect comparisons) often relies on insufficient empirical data. Researchers typically divide the development stages of new China into different historical periods and compare the status attainment patterns of different population groups born in the same period or entering the labor market at the same time to reflect changes in the social stratification mechanism across different periods in China. This approach assumes that the effects of different mechanisms (variables) within the same period (group) remain constant, ignoring the heterogeneity of intra-group effects.\u003c/p\u003e \u003cp\u003eUnlike previous studies that divide historical stages based on major historical events, this study combines repeated survey data from the \"China General Social Survey (CGSS)\" from 2003 to 2017 (urban samples). A continuous sample(n\u0026thinsp;=\u0026thinsp;43235) containing 68 cohorts (1950\u0026ndash;2017) was constructed based on people's year of entry. Through a mixed effects model, the study focuses on analyzing the impact of education level (including whether one has received university education) and party membership on people's occupational status attainment. It also examines whether these impacts show different trends depending on the time people entered the labor market, thereby addressing the shortcomings of historical periodization methods.\u003c/p\u003e"},{"header":"2. Human Capital, Political Capital, and Status Attainment","content":"\u003cp\u003eThe status attainment model suggests that in industrialized societies, individuals' occupational status is primarily constrained by ascriptive factors and achievement factors. As the level of industrialization increases, the role of achievement factors in status attainment becomes more significant (Blau and Duncan 1967). This viewpoint has been widely validated in industrialized countries in Europe and America (Erikson and Goldthorpe 1992). In domestic studies on status attainment in China, it has also received support from various research data (Li \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Xu \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the rich extensions made by both domestic and foreign research based on the classic status attainment model\u003csup\u003e2\u003c/sup\u003e\u0026mdash;such as expanding explanatory and predictive variables and adding structural variables (like social networks) to individual variables (Zhou \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)\u0026mdash;the core assumptions of the classic model remain unchanged. These assumptions posit that in industrialized countries, social stratification mechanisms are relatively stable across generations and individual life processes. Once historical and cultural factors of different societies are controlled, the intergenerational mobility opportunities between fathers and sons remain constant, known as the \"FJH hypothesis\" (Featherman, Jones, and Hauser 1975). This hypothesis statistically assumes that the mechanisms of various explanatory variables do not change with structural variables such as time or space.\u003c/p\u003e \u003cp\u003eIn contrast to the classic status attainment model, which emphasizes that industrial development brings about changes in opportunity structures and leads to the varying roles of family background and human capital in status attainment, the socio-economic development in China since the founding of the People's Republic has gone through different historical stages. China's industrialization process has also been accompanied by a transition from a redistributive economy to a market economy. Each stage exhibits distinct differences in national policies and political processes, including economic development goals, ideology, distribution of educational opportunities, and degree of marketization.\u003c/p\u003e \u003cp\u003eZhou and his research partners argue that compared to market-oriented societies, under the national socialist system, people's life opportunities are not only constrained by the unique redistributive institutions of the state but also significantly influenced by changes in macro political and state policies (Zhou, Tuma, and Moen 1996).\u003c/p\u003e \u003cp\u003eFollowing the model of status attainment, scholars studying the status attainment in China have conducted comparative studies on the relative effects of human capital and family background. While there have been numerous explorations, these studies are often theoretically constrained by the framework of the Blau-Duncan model. A significant theoretical advancement is the exploration of the impact of human capital and political capital on status attainment following the transition from a redistributive to a market economy. Victor Nee introduced the \"market transition theory\" (Nee 1989), which posits that market and redistributive economies are fundamentally different economic systems, each associated with distinct social stratification mechanisms. The market economy is said to enhance job opportunities and increase market power for individuals with higher education, while diminishing the political power of cadres in the allocation of market resources. This theory has ignited a robust debate among scholars of social stratification regarding the stratification model in transitional states, particularly focusing on the advantageous position of political power in the resource allocation process (Bian and Logan 1996; Lin 1995; Parish and Michelson 1996; Rona-Tas 1994; Walder 1995a). The market transition theory continues to evolve, addressing criticisms by highlighting that market reforms are characterized by locality, relativity, and path dependence (Cao and Nee 2000; Nee 1991; Nee and Matthews 1996; Nee and Cao 1999). Despite the ongoing role of redistributive power, empirical studies support the increasing influence of education on income returns since the market transition, which complicates the process of status attainment under the national socialist system.\u003c/p\u003e \u003cp\u003eThe market transition theory and various competitive perspectives predominantly consider income return as the variable of interest, bypassing direct class analysis. However, at their core, these theories essentially address whether the opportunity to become elite after marketization leans towards individuals with higher human capital or continues to necessitate political capital as a prerequisite for reaching elite status (Bian 2002). Research on the status attainment of socialist elites provides a direct response to this question.\u003c/p\u003e \u003cp\u003eStudies by Szelenyi and Martin (1988) on the socialist transformation in Eastern European countries propose that due to the weak economic foundation of socialist regimes, these regimes should place significant emphasis on professional skills and advanced management experience for the rational needs of economic development and military competition. This provides a structural position for intellectuals to become a new class\u0026mdash;technical bureaucrats. Walder suggests that socialist elites comprise two types: those who are politically loyal but lack strong professional skills, and those who are not politically loyal but possess professional skills. Accordingly, there are two distinct upward mobility career paths in socialist countries, leading to different elite positions through selective political review and acceptance. For those preparing for a political career, superiors primarily assess them based on their education and political loyalty, prioritizing their admission to the party. Conversely, for those preparing for a professional career, selection is based on their education, with political loyalty not being the main criterion for promotion, and superiors do not prioritize their admission to the party (Walder 1995b).\u003c/p\u003e \u003cp\u003eNumerous empirical studies have found that with the deepening of market transformation, this dual-path model for elite status attainment has not significantly changed. Party members, especially those who join the party early in their careers, enjoy advantages in promotion and resource allocation (Bian, Shu, and Logan 2001; Zang 2001). This leads most stratification scholars to believe that political inequality based on party membership forms the core of the stratification order in socialist countries (Li and Walder 2001). On the other hand, education, especially university education, significantly impacts both career paths of management elites and professional elites (Walder, Li, and Treiman 2000). Subsequent studies have refined the types of socialist elites, such as government system elites and party system elites (Zang 2001), system insiders and system outsiders (market elites) (Lv and Fan \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), thus enriching the dual-path model.\u003c/p\u003e \u003cp\u003eZhou argues that the dual-path model emphasizes a stable institutional foundation, which results in the continued existence of two segmented career development paths in the Chinese bureaucratic system. However, Zhou underscores the influence of macro political processes on bureaucratic career patterns more. Macro political processes encompass two aspects: changes in state policies affect bureaucratic career patterns by altering selection criteria for official recruitment and promotion, and the inherent tension between centralized states and bureaucratic interests leads to frequent bureaucratic system reforms and political movements, disrupting career patterns. Significant changes in political opportunities across different historical periods have resulted in major differences in life opportunities for labor employment among different age groups (Zhou \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn previous studies examining the influence of human capital and political capital on the process of status attainment, two points are particularly worth discussing. First, income is often used as the core explanatory variable, with less focus on occupational status research. Elite research tends to dominate occupational status studies, leaving general social status attainment relatively underexplored. This is largely because many scholars believe that under the planned economic system, China did not have a real labor market. Labor was considered a national resource, centrally allocated and controlled by the state. There was no free movement of labor, and unemployment was not a concern. The labor market only began to form and align with the characteristics of a market-oriented society after the reform and opening up (Huang \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The system transformation subsequently strengthened the significance of occupational status (Bian, Li, and Li et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The absence of a labor market does not mean that there was no occupational differentiation in socialist society. This study argues that the previous research viewpoint on elite status attainment\u0026mdash;that China's occupational mobility mechanism is a unique mixture of loyalty to the political system and the meritocratic principles of modern occupational mobility (Li and Walder 2001)\u0026mdash;also applies to the attainment of non-elite status. During the transition from a redistributive system to a market-oriented system, the roles and mechanisms of human capital and political capital varied across different historical stages due to differences in macro political processes.\u003c/p\u003e \u003cp\u003eSecond, in terms of research design, previous studies typically divided the history of New China into different stages based on major historical events and compared the status attainment patterns across these stages. In early empirical studies, scholars often used the Cultural Revolution (1966) as a benchmark for dividing historical periods when analyzing the differences in status attainment between the socialist system and the Cultural Revolution period (Parish 1984; Whyte and Parish 1984). When studying status attainment since the market transition, the reform and opening up is usually used as the dividing line, often splitting the period into before 1979 and after 1979 (Li \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Zhou et al. (1996) in dynamic stratification model studies divided the history of New China into three stages: 1949\u0026ndash;1965, 1966\u0026ndash;1979, and 1980\u0026ndash;1994. With the availability of more survey data, later scholars further subdivided the period since the reform and opening up. For instance, Wu (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and Wu (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) used 1986 as a dividing line, splitting the period into 1978\u0026ndash;1986 and 1987\u0026ndash;1996. Some scholars used 1992 (Deng Xiaoping's Southern Tour Speech) and 2002 (the convening of the Sixteenth Party Congress) as dividing lines, categorizing the reform and opening up into the early stage, deepening stage, and comprehensive deepening stage.\u003c/p\u003e \u003cp\u003eAs Lv and Fan (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) divided the status attainment of urban and rural elites in China into three historical stages: 1978\u0026ndash;1992, 1993\u0026ndash;2002, and 2003\u0026ndash;2010. By comparing the status attainment patterns across different historical stages using historical periodization, this approach can generally reflect the differences in status attainment of the Chinese population over time. It can also illustrate the impact of major historical events or national policies on people's life trajectories, as well as compare the relative importance of human capital and political capital at different times. However, this discontinuous division implies a homogeneity assumption of status attainment patterns within different stages (Fang and Feng \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). That is, it assumes that the effect of the independent variable on the dependent variable remains constant within the same historical stage, which may not be an ideal research design method\u003csup\u003e3\u003c/sup\u003e. This study attempts to analyze the role and trend of human capital and political capital in occupational status attainment by constructing a sample database with specific year information, rather than dividing historical stages.\u003c/p\u003e"},{"header":"3. Research Design","content":"\u003cp\u003e \u003cb\u003e(1) Measurement\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDependent Variable\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe dependent variable in this study is occupational status, measured using the International Socio-Economic Index (ISEI) of occupational status for individuals' current or last job. This is a continuous variable ranging from 16 to 90.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIndependent Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe core variables of this study are human capital and political capital, measured by education level and party membership, respectively. Education is measured in two ways: Years of Education: Based on individuals' educational background. University Education: Categorizes individuals based on their highest degree to determine if they have received an university education (1 for yes and o for no), thus observing the role of a college degree in occupational status attainment.\u003c/p\u003e \u003cp\u003eParty membership is measured based on people's political identity, where party members are coded as 1 (including a small number of members from democratic parties), and non-party members are coded as 0.\u003c/p\u003e \u003cp\u003e \u003cb\u003eControl Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGender: Male is coded as 1, female as 0. Current Household Registration: Urban household registration is coded as 1, agricultural household registration as 0. Father's Education Level: Measured based on the father's education level when the respondent was aged 14 (or 18), converted to years of education using the same conversion method as above. Father's Occupational Status: Measured based on the International Socio-Economic Index (ISEI) for the respondent's father when the respondent was aged 14 (or 18). Entry Time: Measured based on the year the respondent first started working.\u003c/p\u003e \u003cp\u003e \u003cb\u003e(2) Data Source\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study merged the urban samples from all 10 waves of the China General Social Survey (CGSS) conducted in 2003, 2005, 2006, 2008, 2010, 2011, 2012, 2013, 2015, and 2017\u003csup\u003e4\u003c/sup\u003e, resulting in a total sample size of 49,403 individuals. The study controlled for the age of respondents between 18 and 65 years old (at the time of the survey) and excluded samples without work experience, resulting in an effective analytical sample of 43,235 individuals. Descriptive statistics for each variable in different survey years are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics of Urban Samples in China General Social Survey CGSS 2003\u0026ndash;2017 (N\u0026thinsp;=\u0026thinsp;43,235)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003ediscrete variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCGSS2003\u003c/p\u003e \u003cp\u003e(4049)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCGSS2005\u003c/p\u003e \u003cp\u003e(4431)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCGSS2006\u003c/p\u003e \u003cp\u003e(4639)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCGSS2008\u003c/p\u003e \u003cp\u003e(3164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCGSS2010\u003c/p\u003e \u003cp\u003e(5272)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCGSS2011\u003c/p\u003e \u003cp\u003e(2310)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCGSS2012\u003c/p\u003e \u003cp\u003e(5148)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCGSS2013\u003c/p\u003e \u003cp\u003e(4957)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eCGSS2015\u003c/p\u003e \u003cp\u003e(3965)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eCGSS2017\u003c/p\u003e \u003cp\u003e(5300)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.8\u003c/p\u003e \u003cp\u003e51.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.2\u003c/p\u003e \u003cp\u003e47.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.6\u003c/p\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.0\u003c/p\u003e \u003cp\u003e48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.6\u003c/p\u003e \u003cp\u003e48.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e53.6\u003c/p\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e48.6\u003c/p\u003e \u003cp\u003e51.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e48.7\u003c/p\u003e \u003cp\u003e51.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003cp\u003e47.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHukou\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAgricultural\u003c/p\u003e \u003cp\u003enon-agricultural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003cp\u003e94.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003cp\u003e90.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003cp\u003e81.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003cp\u003e79.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.4\u003c/p\u003e \u003cp\u003e73.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003cp\u003e69.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003cp\u003e69.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003cp\u003e66.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003cp\u003e64.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e37.2\u003c/p\u003e \u003cp\u003e62.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity Educational\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.5\u003c/p\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.6\u003c/p\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.9\u003c/p\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.2\u003c/p\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e75.8\u003c/p\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e73.4\u003c/p\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003cp\u003e26.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e73.4\u003c/p\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e68.8\u003c/p\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParty membership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNon-Party Members\u003c/p\u003e \u003cp\u003eParty members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79.7\u003c/p\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87.1\u003c/p\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.5\u003c/p\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84.3\u003c/p\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e86.5\u003c/p\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e85.3\u003c/p\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e87.4\u003c/p\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e87.5\u003c/p\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e87.0\u003c/p\u003e \u003cp\u003e13.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003econtinuous variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCGSS2003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eCGSS2005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eCGSS2006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eCGSS2008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCGSS2010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eCGSS2011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eCGSS2012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eCGSS2013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eCGSS2015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003eCGSS2017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eISEI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[16, 90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.7(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.3(15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.3(13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.9(17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40.3(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.3(16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e40.6(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e39.8(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e39.9(16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e42.2(15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[18, 65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.6(11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.3(11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.4(12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.6(12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.7(12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e43.0(12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e43.2(12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43.2(12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e43.6(12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.3(12.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eYears of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0, 20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.8(3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.4(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.5(3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.6(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.7(3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.6(3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.8(3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.7(3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e10.7(4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e11.0(4.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eYears of father's education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0, 20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.1(4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.2(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.4(4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.3(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.2(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.3(4.5) )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.3(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.2(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6.0(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6.2(4.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ethe ISEI of father\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[16, 90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.6(19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.5(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.7(15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.3(20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.4(15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35.5(16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e35.4(16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e33.9(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e30.7(18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e34.8(16.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003e(Note: Discrete variables are percentages in the cells, and continuous variables are means (standard deviations) in the cells.)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e(3) Analysis Model\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study divided the respondents into different groups based on their year of entry (1944\u0026ndash;2017). Due to the limited number of samples entering before 1950, these samples were grouped into the year 1950. A total of 68 entry year cohorts from 1950 to 2017 were obtained. A mixed effects model was then used to analyze the impact of factors such as human capital and political capital on occupational status.\u003c/p\u003e \u003cp\u003eUnlike previous studies that divided years into different birth cohorts or major event periods, this study used specific years as stratification variables, which provides more detail and eliminates concerns about the accuracy of group division. Using time as a stratification variable is an important means of analyzing repeated survey data, known as \"pseudo-panel data,\" where each sample appears only once in the survey. This approach avoids the autocorrelation issues associated with repeated sample surveys (longitudinal data) or time series data, and can reflect the changing trend of sample means over time.\u003c/p\u003e \u003cp\u003eDepending on the different measurement methods of the dependent variable, A mixed OLS model is used. The statistical model was divided into two levels:\u003c/p\u003e \u003cp\u003eLevel 1. is an individual-level model:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${ISEI}_{ij}=\\beta \\text{0}\\text{j}+\\beta \\text{1}\\text{j}\\text{*}\\text{g}\\text{e}\\text{n}\\text{d}\\text{e}\\text{r}+\\beta \\text{2}\\text{j}\\text{*}\\text{h}\\text{u}\\text{k}\\text{o}\\text{u}+\\beta \\text{3}\\text{j}\\text{*}\\text{e}\\text{d}\\text{u}+\\beta \\text{4}\\text{j}\\text{*}\\text{p}\\text{a}\\text{r}\\text{t}\\text{y}+\\beta \\text{5}\\text{j}\\text{*}\\text{e}\\text{d}\\text{u}\\_\\text{f}+\\beta \\text{6}\\text{*}\\text{i}\\text{s}\\text{e}\\text{i}\\_\\text{f}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eLevel 2. is a random year effect model:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\({\\beta _{kj}}={\\gamma _{k0}}+{\\mu _{kj}}\\)\u003c/span\u003e \u003c/span\u003e, [k\u0026thinsp;=\u0026thinsp;0, 3, 4]\u003c/p\u003e \u003cp\u003eIn these models, i represents the individual, j represents the year of entry, and k correspond to the intercepts and the coefficients of the independent variables. This study focuses on the impact of education and party membership variables on status attainment and trends over time. For simplicity, the random effects of gender, birthplace, father's education level, and occupational status variables are fixed at 0. All continuous variables in the analysis model are centered based on the year of entry (i.e., centered around the group average).\u003c/p\u003e"},{"header":"4. Data Analysis","content":"\u003cp\u003e \u003cb\u003e(1) Mixed Effects Model Construction\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo analyze the factors influencing occupational status, this study employs a mixed effects model using the respondent's current or last occupation's Index of Socioeconomic Status (ISEI) as the dependent variable. The year of initial job entry is used as a stratification variable. The models are constructed as follows:\u003c/p\u003e \u003cp\u003eModel 1: Null Model\u003c/p\u003e \u003cp\u003eThis model includes only the intercept term and random effects of the intercept. The intercept represents the average occupational status of the total sample, while the random effects capture the variation in occupational status for samples entering in different years.\u003c/p\u003e \u003cp\u003eModel 2: Fixed Effects Model\u003c/p\u003e \u003cp\u003eThis model adds explanatory and control variables. Except for the intercept, the effects of each variable are fixed, making this model similar to a regular regression model that does not account for year differences.\u003c/p\u003e \u003cp\u003eModel 3: Random Effects Model\u003c/p\u003e \u003cp\u003eBuilding on Model 2, this model allows for intergroup differences in the impact of education level and party membership variables on individuals' occupational status.\u003c/p\u003e \u003cp\u003eModel 4: University Education Impact Model\u003c/p\u003e \u003cp\u003eIn this model, the education level variable in Model 3 is replaced with a dummy variable indicating whether the individual has received university education. This model focuses on the impact of university education on individuals' occupational status and its changing trends.\u003c/p\u003e \u003cp\u003eThe estimation results for these models are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMixed Effects Analysis of the Factors Influencing ISEI (n\u0026thinsp;=\u0026thinsp;43,235, N\u0026thinsp;=\u0026thinsp;68)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003efixed effects\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003emodel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003emodel 4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.16***\u003c/p\u003e \u003cp\u003e(0.841)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.28***\u003c/p\u003e \u003cp\u003e(0.861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.29***\u003c/p\u003e \u003cp\u003e(0.883)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.33***\u003c/p\u003e \u003cp\u003e(0.564)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.969***\u003c/p\u003e \u003cp\u003e(0.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.989***\u003c/p\u003e \u003cp\u003e(0.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.409**\u003c/p\u003e \u003cp\u003e(0.128)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHukou (agricultural\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.346***\u003c/p\u003e \u003cp\u003e(0.163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.354***\u003c/p\u003e \u003cp\u003e(0.163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.323***\u003c/p\u003e \u003cp\u003e(0.159)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.865***\u003c/p\u003e \u003cp\u003e(0.024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.879***\u003c/p\u003e \u003cp\u003e(0.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecollege (no\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.550***\u003c/p\u003e \u003cp\u003e(0.383)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParty (no\u0026thinsp;=\u0026thinsp;0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.594***\u003c/p\u003e \u003cp\u003e(0.195)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.301***\u003c/p\u003e \u003cp\u003e(0.395)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.690***\u003c/p\u003e \u003cp\u003e(0.504)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eyears of education of father\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.111***\u003c/p\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.109***\u003c/p\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.202***\u003c/p\u003e \u003cp\u003e(0.018)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ethe occupational status (ISEI) of father\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.047***\u003c/p\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.047***\u003c/p\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0602***\u003c/p\u003e \u003cp\u003e(0.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erandom effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evariance components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003evariance components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003evariance components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003evariance components\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.718***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.208***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.763***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.492***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.056***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.819***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.690***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.581***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eresiduals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e233.428***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e169.883***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168.823***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e172.039***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e358759.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e345077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e344960.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e345750.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e358785.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e345155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e345056.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e345846.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog likelihood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-179376.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-172529.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-172469.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-172864.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e(2) Changes in the Trend of Occupational Status Attainment with Entry Time\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBy comparing the random effects of intercept terms in Models 1\u0026ndash;4, significant differences in intercept terms across different years of entry were observed. Taking Model 3 as an example, the intercept term represents the occupational status of non-party female agricultural hukou holders with average education levels and family background (father's education and occupational status). To illustrate the trend of their average occupational status over time, this study calculated the mixed effects of the intercept and plotted Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFrom Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, it can be seen that the average occupational status of individuals shows an overall increasing trend year by year:\u003c/p\u003e \u003cp\u003eFirst, Early Days of the Founding of the Country (1949\u0026ndash;1956): During the period of socialist revolution, the national economic strategy was guided by the \"one transformation, three reforms\" general line, which thoroughly transformed individual industrial and commercial enterprises and capitalist industrial and commercial enterprises (the destratification social experiment) (Parish 1984). This established a state socialist redistributive economic system based entirely on public ownership, essentially eliminating the private economy and making the class structure more uniform. During this stage, the average occupational status of people showed a declining trend.\u003c/p\u003e \u003cp\u003eSecond, Post-Socialist Transformation Period: After the completion of socialist transformation, China entered a period of rapid development. Despite the impacts of the Great Leap Forward and major natural disasters, the average occupational status of people continued to increase significantly.\u003c/p\u003e \u003cp\u003eThird, Cultural Revolution (1966\u0026ndash;1976): The occurrence of the Cultural Revolution led to a large number of educated youths being sent to the countryside, resulting in a significant decline in people's occupational status. This trend continued until after the end of the Cultural Revolution in 1976.\u003c/p\u003e \u003cp\u003eForth, Reform and Opening Up (Post-1978): Following the reform and opening up in 1978, China transitioned from a redistributive economy to a market economy, with the degree of marketization continuously increasing. Consequently, people's average occupational status continued to rise.\u003c/p\u003e \u003cp\u003eThe analysis of the average trend of people's occupational status indicates that in a relatively stable political environment, with the development of the national economy and the improvement of industrialization levels, people's average occupational status will continue to rise. However, during sensitive periods, people's average occupational status is susceptible to macro-political interference.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e(3) Trends in the Time Changes of Occupational Status Attainment Influenced by Educational Level\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges in the Effects of Years of Education\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe impact of education level (fixed effect) is consistent with previous studies, showing that education level has a significant positive effect on improving people's occupational status. For every additional year of education, the average increase in occupational status is around 1.879 points. However, the effect of education level varies significantly between different entry years, as indicated by the significant variance components.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the impact and changing trends of education years on people's occupational status. Analysis reveals that the influence of education level on occupational status shows multiple fluctuations:\u003c/p\u003e \u003cp\u003eFirst, Early Days of the Country's Founding: During the transitional period, the general line led to the transformation of individual industrial and commercial economies and capitalist industrial and commercial economies. Individuals with higher education levels, such as individual business owners and private entrepreneurs, largely disappeared and joined the ranks of the working class, resulting in downward mobility from an occupational stratification perspective.\u003c/p\u003e \u003cp\u003eSecond, Post-Transformation Industrial Development: After the completion of the socialist transformation, China entered a period of industrial development, despite encountering major historical events such as the Great Leap Forward and natural disasters. The effects of industrial development became apparent, and the influence of education level on occupational status gradually strengthened, initially reflecting the positive role of education in an industrial society.\u003c/p\u003e \u003cp\u003eThird, Cultural Revolution: During the Cultural Revolution, economic development stagnated, and the influence of education on occupational status gradually declined. This trend continued until the end of the Cultural Revolution.\u003c/p\u003e \u003cp\u003eForth, Reform and Opening Up: The beginning of reform and opening up alleviated the decline in the influence of education on occupational status. The role of education level in influencing occupations strengthened, aligning with the expectations of market transformation theory.\u003c/p\u003e \u003cp\u003eFifth, Popularization of Nine-Year Compulsory Education (1992): With the popularization of nine-year compulsory education, the education level of the labor force entering the market significantly improved, leading to a brief slight decline in the role of education. This trend continued until around 2000 when the role of education level rose again.\u003c/p\u003e \u003cp\u003eLast, Higher Education Expansion (1999): Due to the large-scale expansion of higher education enrollment in 1999, the number of college students surged, leading to a decline in the advantage of education level around 2005. This decline almost continued until the end of the research data year.\u003c/p\u003e \u003cp\u003eDespite the multiple fluctuations in the role of education level in occupational status attainment, the positive effect of education on status attainment remained consistent (there was no year when the educational effect was negative). The market transformation theory explains the impact of education on status attainment in the early stages of reform and opening up, but this process is also regulated by other national policy processes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges in the Role of Higher Education\u003c/b\u003e \u003c/p\u003e \u003cp\u003eModel 4 specifically analyzed the impact of university education on people's occupational status. The results indicated that individuals who had received university education had an average occupational status that was 13.550 points higher compared to those with a high school education or below.\u003c/p\u003e \u003cp\u003eTo understand the role of higher education in occupational status attainment, it is essential to consider the development of higher education in New China. According to national statistical data\u003csup\u003e5\u003c/sup\u003e: In 1949, at the establishment of New China, the proportion of university students in the total population was only 2.2 per 10,000 people. By 1978, after the resumption of the college entrance examination, this proportion had increased to 8.9 per 10,000 people. By 1998, it had further increased to 51.9 per 10,000 people. Following the expansion of university enrollment in 1999, the scale of university students continued to increase, reaching 257.6 per 10,000 people by 2017\u0026mdash;five times the scale before the expansion.\u003c/p\u003e \u003cp\u003eUniversity education has gradually shifted from elite education to mass education. As a result, university students face increasing competition in the labor market, prompting many to pursue graduate studies to alleviate employment pressure and enhance their human capital, thereby maintaining an advantage in the labor market.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the impact of university education on occupational status and its changing trends over time. Key observations include:\u003c/p\u003e \u003cp\u003eFirst, Before the Resumption of the College Entrance Examination: The proportion of university students in China was very low. Among samples entering the workforce from 1950 to 1955, no university students were selected, so only the average value trend line is shown in the figure. Before 1965, the number of university student samples was also less than 10, possibly leading to statistical bias. Therefore, the trend reflected in the figure before 1965 may not be accurate.\u003c/p\u003e \u003cp\u003eSecond, Early Stages of the Cultural Revolution: Due to the policies targeting intellectuals and the movement of educated youth going to the countryside, the impact of university education on occupational status experienced a rapid decline. This is consistent with the findings of Zhou et al. (2015) on the stratified dynamic process theory. However, this trend began to reverse in the later stages of the Cultural Revolution as the scale of educated youth going to the countryside decreased, and some policies relaxed, allowing early educated youth to return to cities.\u003c/p\u003e \u003cp\u003eThird, Post-Cultural Revolution and Reform Period: After the resumption of the college entrance examination in 1977, the scale of university education in China increased. However, as China had not yet formed a labor market, the employment of university graduates still followed the \"allocation\" model, and university education did not receive the expected status returns from market transformation theory. The relative importance of university education to occupational status decreased, contrary to the expectations of market transformation theory.\u003c/p\u003e \u003cp\u003eForth, Post-2000 Trends: The overall return of university education to occupational status continued to decline, but the rate of decline slowed compared to earlier years. In 1996, the country gradually abolished the allocation system for graduates, allowing for a two-way selection between graduates and employers, theoretically increasing the role of higher education in status attainment. However, the rapid increase in the supply of talent due to higher education expansion led to increased employment difficulties for college students, further devaluing university degrees. To counter this, many university graduates pursued postgraduate studies. Post-2010, the occupational status and returns of university graduates increased again, mainly due to a significant proportion of postgraduates in the sample.\u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e together indicate that while the impact of education level on occupational status has a positive effect, its effectiveness has fluctuated under different socio-economic systems and market transformations. Before the reform and opening up, especially during the Cultural Revolution, the relative effect of education level declined. Since the reform, although the role of education level in status attainment has strengthened, the increased supply of highly educated talents has led to signs of degree devaluation rather than sustained enhancement.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e(4) The Time Trend of the Influence of Party Membership on the Attainment of Occupational Status\u003c/b\u003e \u003c/p\u003e \u003cp\u003eParty membership has a significant impact on people's current (or last) occupational status. Compared to non-party members, the average occupational status of party members is about 6.3\u0026ndash;6.7 points higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, see Models 2 to 4). However, the role of party membership also varies significantly over different periods.\u003c/p\u003e \u003cp\u003eAs depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the influence of party membership on occupational status shows a trend similar to that of higher education, given that opportunities for higher education and party membership often intertwine\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFirst, From the Founding of the Country to the Cultural Revolution: During this period, the role of party membership in people's occupational status continued to strengthen, reflecting the significant advantage of party members in resource allocation under the redistributive system.\u003c/p\u003e \u003cp\u003eSecond, Cultural Revolution: During the Cultural Revolution, the role of party membership experienced a V-shaped trend of decline followed by an increase.\u003c/p\u003e \u003cp\u003eThird, Post-Reform and Opening Up (1978 onwards): After the reform and opening up, the importance of party membership declined again. Over the past decade or so since 2000, the effect of party membership has fluctuated slightly below the average effect. This is consistent with the expectations of market transition theory, as the role of political capital begins to relatively decline after experiencing market-oriented reforms.\u003c/p\u003e \u003cp\u003eForth, Post-2000 Trends: Under the influence of higher education expansion, to alleviate employment difficulties and comply with the needs of state organizations, the number of university graduates participating in civil service examinations, \"three supports and one assistance,\" and other programs has increased. In the selection for these organizations, political qualities are continuously emphasized as an important criterion. After 2010, the occupational status returns for party members began to rise again, and from the slope perspective, the upward trend is very steep.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5. Conclusion and Discussion","content":"\u003cp\u003e \u003cb\u003e(1) Overview\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe dynamic process of social status attainment, as a key aspect of social stratification, underscores the elasticity of social structure. The classic status attainment model, rooted in the development of industrial society, suggests that the constraints of ascriptive factors on an individual's socioeconomic status will diminish over time, while the influence of achievement factors will grow, indicating a move towards a more open social structure and a decrease in social inequality levels. However, the trajectory of New China's industrial development, marked by significant political events and policy shifts, diverges from traditional industrialization logic. After embracing market-oriented reforms, transitioning from a state socialist redistribution system to a market economy introduced notable shifts in the mechanisms of social stratification across different historical stages.\u003c/p\u003e \u003cp\u003e \u003cb\u003e(2) Theoretical Implications\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSolely applying the industrialization logic to analyze the changes in Chinese people's status attainment mechanisms\u0026mdash;by examining family background and human capital factors\u0026mdash;may not yield theoretical breakthroughs. For countries undergoing socialist transition, the interplay between redistribution logic, marketization logic, and the sustained advantage of political power in resource allocation garners significant theoretical interest.\u003c/p\u003e \u003cp\u003eMarket transformation theory posits that with marketization advancement, the advantage of redistributive power should gradually cede to market forces. However, empirical evidence challenges this notion, revealing that political power retains a continuous advantage in income returns and elite status attainment during the socialist transformation. Human capital's role is also on the rise, creating a dual pathway alongside political capital for forming socialist elites.\u003c/p\u003e \u003cp\u003e \u003cb\u003e(3) Empirical Findings\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study leverages data from the China General Social Survey (CGSS) spanning 2003 to 2017 to examine the impact and trends of education level and party membership on individuals' occupational status. Findings indicate a steady increase in the average occupational status of Chinese people and their opportunities to ascend to elite positions, albeit with occasional declines.\u003c/p\u003e \u003cp\u003e \u003cb\u003e(4) Key observations include\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eEducation Level: Positively impacts average occupational status, though its influence significantly fluctuates across different historical periods. Early market transformation stages saw a notable increase in education's role in status attainment, which later declined with higher marketization levels, expansion of higher education, and policy changes, contradicting market transformation expectations.\u003c/p\u003e \u003cp\u003eParty Membership: The role of party membership has experienced significant shifts over time. Initially, its advantages in attaining professional status diminished but have seen a resurgence in recent years, particularly as political qualities gain prominence in selection processes for political organizations.\u003c/p\u003e \u003cp\u003e \u003cb\u003e(5) Reflections and Directions for Future Research\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study's findings highlight the nuanced and heterogenous effects of human capital and political capital across different periods, suggesting that macro factors not yet observed may influence or constrain status attainment processes. The observed V-shaped changes in the influence of university education and party membership during the Cultural Revolution underscore the complexity of status attainment mechanisms during different historical phases. This complexity suggests that simplifying China's social stratification mechanisms based solely on major events may overlook critical nuances, emphasizing the need for detailed examination under appropriate conditions.\u003c/p\u003e \u003cp\u003eIn summary, while historical events provide a general framework for understanding social change in China, they may not fully capture the intricate dynamics of social stratification mechanisms. Future research should continue to explore these complexities, considering the multifaceted interactions between human capital, political capital, and broader socio-political contexts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. This data can be found here: http://www.cnsda.org/index.php?r=projects/index.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical review and approval were not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Social Science Foundation of China project \u0026quot;Research on the Constraints and Mechanisms of Health Equality in the Context of the Healthy China Strategy (Grant no.21BSH008).\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Social Survey Center of Renmin University of China for providing data for the research, and to all the project team participants and interviewees.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXxx was responsible for the framework and idea of the entire text, data processing and analysis, and wrote the initial draft of this study. The author takes full responsibility for this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBian Yanjie. 2002. \u003cem\u003eMarket Transformation and Social Stratification: American Sociologists Analyze China\u003c/em\u003e (Chinese). Beijing: Sanlian Bookstore.\u003c/li\u003e\n \u003cli\u003eBian, Yanjie., Li, Lulu., Li, Yu., et al., 2006, Structural Barriers, Institutional Transformation and Status Resource Content, \u003cem\u003eChinese Social Sciences(Chinese)\u003c/em\u003e. 5:100-109.\u003c/li\u003e\n \u003cli\u003eBian, Yanjie and John R. Logan. 1996. \u0026quot;Market Transition and the Persistence of Power: The Changing Stratification System in Urban China.\u0026quot; \u003cem\u003eAmerican Sociological Review\u003c/em\u003e 61(5):739-758.\u003c/li\u003e\n \u003cli\u003eBian, Yanjie, Xiaoling Shu and John R. 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Beijing: Renmin University of China Press.\u003c/li\u003e\n \u003cli\u003eZhou, Yi. 2009, After the Blau-Duncan model: transformation or challenge, \u003cem\u003eSociological Research (Chinese)\u003c/em\u003e. 6:206-225.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e This study uses data from the \"China General Social Survey (CGSS)\" project hosted by the China Survey and Data Center of Renmin University of China. The authors thank this institution and its staff for providing data assistance, and take full responsibility for the content.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e In the research on the attainment of general social status in China, researchers not only focus on the impact of variables such as family background and education on people's social status attainment, but also pay attention to the role of intermediate mechanisms such as family cultural capital, social networks (capital), and political capital. In terms of outcome variables, in addition to focusing on occupational status, attention is also paid to education level, income status, party membership opportunities, unit type, and level, among others. There is a lot of literature on this topic, not listed one by one.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Zhou (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) pointed out that when analyzing the impact of dynamic processes on people's life opportunities, the ideal research design is to use a prospective research design to track a representative individual sample. However, due to historical or political reasons, this research design cannot be implemented. An alternative approach is to collect people's life event history information at different stages through a retrospective design (the method used by Zhou et al.), or to use time-repeated samples to measure the changes and persistence of individual life opportunities over time (as used in this study).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The data and sampling design for all waves of the China General Social Survey (CGSS) can be obtained through the China Social Survey and Data Center at Renmin University of China (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://nsrc.ruc.edu.cn/\u003c/span\u003e\u003cspan address=\"http://nsrc.ruc.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the National Survey Data Archive website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cnsda.ruc.edu.cn/\u003c/span\u003e\u003cspan address=\"http://cnsda.ruc.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Data source: \"Statistical Data Compilation of Fifty Years of New China (1949\u0026ndash;1999)\" and other corresponding yearbooks.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e The Pearson correlation coefficient of the mixed effects of the two reached 0.696.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Social transformation, education level, party membership, occupational status attainment, repeated cross-sectional design","lastPublishedDoi":"10.21203/rs.3.rs-4591449/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4591449/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevious researches on the occupational status attainment among Chinese residents have predominantly employed grouped regression analysis, which categorizes data according to significant historical events. This approach explores how variables such as education and party membership influence status attainment across different time periods. However, it often overlooks the heterogeneity of effects within these groups. To address this gap, the present study utilizes urban sample data from the \"China General Social Survey (CGSS)\" spanning from 2003 to 2017(n=43,235)\u003csup\u003e1\u003c/sup\u003e. It segments the population into 68 cohorts based on individuals' year of entry from 1950 to 2017, thereby concentrating on the evolving impacts of education level and party membership on occupational status attainment post the establishment of New China. The findings reveal a continuous overall increase in average occupational status since the founding of New China. Both education level and party membership positively correlate with status attainment; however, their relative significance exhibits considerable variation across different eras. These results both corroborate and challenge prior studies concerning status attainment. While the method of grouped regression analysis based on major historical events effectively captures the general shift from a redistributive to a market economy, it fails to sufficiently account for the nuanced impacts of social change on occupational status attainment. This study underscores the need for more detailed analyses to comprehensively understand these dynamics.\u003c/p\u003e","manuscriptTitle":"Education, Party Membership, and Occupational Status Attainment in China's Social Transformation (1950-2017)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-24 11:01:41","doi":"10.21203/rs.3.rs-4591449/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"81cfbb65-a3cd-41e7-8f8d-ad21c811852a","owner":[],"postedDate":"February 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44540944,"name":"Social science/Development studies"},{"id":44540945,"name":"Social science/Sociology"},{"id":44540946,"name":"Social science/Education"}],"tags":[],"updatedAt":"2025-02-24T11:01:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-24 11:01:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4591449","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4591449","identity":"rs-4591449","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}