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This paper analyzes job burnout of inside-system legal professionals under the rule-of-law reform in China and its possible causes. Social cognitive theory, including cognitive dissonance, expectancy theory, and social comparison theory, provides the analytic framework for this study. The conclusion reveals a relatively high level of job burnout among inside-system legal professionals in China. Further analysis indicates that the individual's commitment to the rule of law, confidence in the legal reform, and practice of non-rule-of-law in daily work are influential factors affecting his/her job burnout levels. Importantly, the interaction coefficients between these variables are statistically significant, clearly demonstrating that the discrepancy between expectation and reality is one of the root causes of job burnout in the legal profession. The discrepancy causes cognitive dissonance and psychological imbalance. At a theoretical level, this finding opens a new way of examining a particular type of occupational burnout. It shows that under the rule-of-law reform, Chinese inside-system legal professionals exhibit cognitive dissonance between ideals and reality, which constitutes a micro-political psychological basis for organizational change as speculated by neo-institutionalists and, in turn, reveals insights that may help us to understand the legal reform process within the bureaucratic system.

AbstractThis study employs sequence analysis to explore the educational pathways of individuals born in China between 1976 and 1988, a cohort that witnessed substantial educational expansion. The study constructs a typology for classifying these educational trajectories and quantifies the prevalence of each category within the cohort. Utilizing decision tree analysis, the study investigates the relationship between different educational pathways and various background characteristics. Unlike the "waning coefficients" commonly observed in Mare model and its variants, this approach unveils the substantial influence of cumulative advantage and disadvantage in shaping educational trajectories, a process heavily impacted by individuals' social backgrounds. Despite some exceptions and complexities, several discernible patterns become apparent. For instance, individuals hailing from rural settings generally exhibit a decreased likelihood of progressing along superior educational trajectories throughout their academic endeavors when juxtaposed with their urban counterparts. Moreover, elevated levels of parental education persistently enhance children's prospects for accessing superior educational pathways, irrespective of their urban or rural origins. This methodology serves as a valuable instrument for scrutinizing the general features and diversity of educational trajectories, providing a complementary perspective to existing research on educational stratification and inequality.

Based on data collected from residential aged care facility websites and the Sixth China National Population Census, this paper studies the spatial pattern of Beijing's aged care resources in the framework of spatial location of public facilities. The results show that at the township/street level, the overall distribution of public aged care resources is relatively balanced, showing positive spatial autocorrelation, while private aged care resources show partially negative spatial autocorrelation. Spatial regression analysis indicates that the dispersed and clustered distribution of private aged care resources are more sensitive to the density of local elderly population, although the distribution of two types of resources is affected by the absolute number of service objects in respective administrative areas. In short, the spatial distribution pattern of public and private aged care resources reflects the contrast between efficiency and equity in providing aging care in China, a fact that is shaped by both administrative and market forces.

AbstractThis study examines sports and physical activities among Chinese aged 18–65, using network analysis on a significant random sample. It categorizes sports into 11 groups based on public selection, with a community detection algorithm aiding classification. Variables like age, gender, and education were integrated, revealing how life stages, gender disparities, and social class influence activity participation. The mixed graph model shows both positive and negative correlations among activities, highlighting the role of sports as both a social integrator and divider, reflective of broader societal norms and inequalities. The exponential random graph model further illustrates a complex network of demographic-driven participation patterns. The purpose of this investigation is twofold: to advance methodological approaches in the study of sports-related social networks and to explore the broader implications such networks may have on individual and collective behaviors within this field.