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  1. Getting the Within Estimator of Cross-Level Interactions in Multilevel Models with Pooled Cross-Sections: Why Country Dummies (Sometimes) Do Not Do the Job

    Multilevel models with persons nested in countries are increasingly popular in cross-country research. Recently, social scientists have started to analyze data with a three-level structure: persons at level 1, nested in year-specific country samples at level 2, nested in countries at level 3. By using a country fixed-effects estimator, or an alternative equivalent specification in a random-effects framework, this structure is increasingly used to estimate within-country effects in order to control for unobserved heterogeneity.
  2. Assessing Differences between Nested and Cross-Classified Hierarchical Models

    Sociological Methodology, Volume 49, Issue 1, Page 220-257, August 2019.
  3. Social Space Diffusion: Applications of a Latent Space Model to Diffusion with Uncertain Ties

    Social networks represent two different facets of social life: (1) stable paths for diffusion, or the spread of something through a connected population, and (2) random draws from an underlying social space, which indicate the relative positions of the people in the network to one another. The dual nature of networks creates a challenge: if the observed network ties are a single random draw, is it realistic to expect that diffusion only follows the observed network ties? This study takes a first step toward integrating these two perspectives by introducing a social space diffusion model.
  4. No Longer Discrete: Modeling the Dynamics of Social Networks and Continuous Behavior

    The dynamics of individual behavior are related to the dynamics of the social structures in which individuals are embedded. This implies that in order to study social mechanisms such as social selection or peer influence, we need to model the evolution of social networks and the attributes of network actors as interdependent processes. The stochastic actor-oriented model is a statistical approach to study network-attribute coevolution based on longitudinal data. In its standard specification, the coevolving actor attributes are assumed to be measured on an ordinal categorical scale.
  5. CASM: A Deep-Learning Approach for Identifying Collective Action Events with Text and Image Data from Social Media

    Protest event analysis is an important method for the study of collective action and social movements and typically draws on traditional media reports as the data source. We introduce collective action from social media (CASM)—a system that uses convolutional neural networks on image data and recurrent neural networks with long short-term memory on text data in a two-stage classifier to identify social media posts about offline collective action. We implement CASM on Chinese social media data and identify more than 100,000 collective action events from 2010 to 2017 (CASM-China).
  6. Women’s Assessments of Gender Equality

    Women’s assessments of gender equality do not consistently match global indices of gender inequality. In surveys covering 150 countries, women in societies rated gender-unequal according to global metrics such as education, health, labor-force participation, and political representation did not consistently assess their lives as less in their control or less satisfying than men did. Women in these societies were as likely as women in index-equal societies to say they had equal rights with men.
  7. Challenging Evolution in Public Schools: Race, Religion, and Attitudes toward Teaching Creationism

    Researchers argue that white evangelical Christians are likely to support teaching creationism in public schools. Yet, less is known about the role religion may play in shaping attitudes toward evolution and teaching creationism among blacks and Latinos, who are overrepresented in U.S. conservative Protestant traditions. This study fills a gap in the literature by examining whether religious factors (e.g., religious affiliation and Biblical literalism) relate to differences in support for teaching creationism between blacks and Latinos compared to whites and other racial groups.
  8. Adverse Childhood Experiences, Early and Nonmarital Fertility, and Women’s Health at Midlife

    Adverse childhood experiences (ACEs) have powerful consequences for health and well-being throughout the life course. We draw on evidence that exposure to ACEs shapes developmental processes central to emotional regulation, impulsivity, and the formation of secure intimate ties to posit that ACEs shape the timing and context of childbearing, which in turn partially mediate the well-established effect of ACEs on women’s later-life health.
  9. ‘‘I Just Need a Job!’’ Behavioral Solutions, Structural Problems, and the Hidden Curriculum of Parenting Education

    Parenting education programs aim to teach parents, often low-income mothers, a set of skills, behaviors, and attitudes believed to promote improved opportunities for their children. Parenting programs are often offered in schools, with instructors teaching pregnant or parenting teens about child development, attachment, and discipline strategies. Despite the large numbers of participants and significant public and private funding going to parenting education, sociologists of education in the United States have paid little attention to the topic.
  10. The Distribution of School Quality: Do Schools Serving Mostly White and High-SES Children Produce the Most Learning?

    What is schools’ role in the stratification system? One view is that schools are an important mechanism for perpetuating inequality because children from advantaged backgrounds (white and high socioeconomic) enjoy better school learning environments than their disadvantaged peers. But it is difficult to know this with confidence because children’s development is a product of both school and nonschool factors, making it a challenge to isolate school’s role.