The interdisciplinary field of knowledge discovery and data mining emerged from a necessity of big data requiring new analytical methods beyond the traditional statistical approaches to discover new knowledge from the data mine. This emergent approach is a dialectic research process that is both deductive and inductive. The data mining approach automatically or semi-automatically considers a larger number of joint, interactive, and independent predictors to address causal heterogeneity and improve prediction. Instead of challenging the conventional model-building approach, it plays an important complementary role in improving model goodness of fit, revealing valid and significant hidden patterns in data, identifying nonlinear and non-additive effects, providing insights into data developments, methods, and theory, and enriching scientific discovery. Machine learning builds models and algorithms by learning and improving from data when the explicit model structure is unclear and algorithms with good performance are difficult to attain. The most recent development is to incorporate this new paradigm of predictive modeling with the classical approach of parameter estimation regressions to produce improved models that combine explanation and prediction.

This article uses event history analyses to examine how the criteria of political screening and educational credentials evolve in the attainment of Ch

This study examined Chinese attitudes toward women's careers, marriage rights, sexual freedom, and the importance of having sons using a 1991 national sample of individuals and community-level data and through a series of nested multilevel models. Education influences gender attitudes in multiple ways at both the micro- and macrolevels. Better-educated individuals hold more egalitarian gender attitudes, and this positive effect of individual education is larger for women than for men, indicating a strong empowerment effect for women. Egalitarian gender attitudes trickle down through education, as individuals in communities with high education are socialized toward more egalitarian attitudes. Community education has a larger effect toward the egalitarian direction on the attitude toward the importance of having sons than on the attitude toward women's marriage rights, indicating that change in the latter attitude occurred earlier and has now spread via education. These findings show that education is a vehicle of socialization that is used by both the domestic power elite (the Communist Party) and the Western culture.

In this article, we examine the relationship between market transition and gender gap in earnings in urban China. We analyze change in the gender gap

It remains unclear to what extent shifts in gender attitudes are products of changes in micro-level characteristics, macro-level social transformations, or net cohort and period transitions. We test these questions on 20 waves of data from the General Social Survey, 1977–2016 (N = 45,125). Compositional change in individual characteristics accounts for almost 78 percent of the cohort variation in gender attitudes, but only 32 percent of the historical transformations. Macro dynamics are responsible for an additional 60 percent of the historical change in gender attitudes. Two structural forces are associated with historical transitions in American gender attitudes: gender equality in the labor force and the rise of men’s overwork. Each of these factors accounts for a significant proportion of the period variation in gender attitudes in our analysis, and the rise of men’s overwork appears to account for the puzzle of the “stalled revolution” in the 1990s and its “restart” in the mid-2000s. The conservative swing in 1994–2004 correlates with the rise of overwork, as the proportion of men who overwork soared during this period when traditional gender roles were reinforced.