American Sociological Association

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  1. Network Effects in Blau Space: Imputing Social Context from Survey Data

    We develop a method of imputing ego network characteristics for respondents in probability samples of individuals. This imputed network uses the homophily principle to estimate certain properties of a respondent’s core discussion network in the absence of actual network data. These properties measure the potential exposure of respondents to the attitudes, values, beliefs, and so on of their (likely) network alters.

  2. Economic Populism and Bandwagon Bigotry: Obama-to-Trump Voters and the Cross Pressures of the 2016 Election

    Through an analysis of validated voters in the 2016 American National Election Study, this article considers the voters who supported Obama in 2012 and Trump in 2016. More than 5.7 million in total, Obama-to-Trump voters were crucial to Trump’s victory in the Electoral College. They were more likely to be white, working class, and resident in the Midwest. They had lower levels of political interest, were centrist in both party affiliation and ideology, and were late deciders for the 2016 election.
  3. 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.
  4. 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).
  5. 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.
  6. The Purposes of Refugee Education: Policy and Practice of Including Refugees in National Education Systems

    This article explores the understood purposes of refugee education at global, national, and school levels. To do so, we focus on a radical shift in global policy to integrate refugees into national education systems and the processes of vernacularization accompanying its widespread implementation. We use a comparative case study approach; our dataset comprises global policy documents and original interviews (n = 147) and observations in 14 refugee-hosting nation-states.
  7. 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.
  8. Numbers, Narratives, and Nation: Mainstream News Coverage of U.S. Latino Population Growth, 1990–2010

    Ideologies that support racial domination and White supremacy remain foundational in U.S. society, even as the nation becomes increasingly diverse and progressively focused on quantitative measurement. This study explores how a prominent mainstream news outlet represents the growth of the nation’s second largest population, Latinos, within this changing demographic and numeric environment.
  9. Do Sociology Courses Make More Empathetic Students? A Mixed-Methods Study of Empathy Change in Undergraduates

    Assessing course goals is often challenging; assessing an abstract goal, like empathy, can be especially so. For many instructors, empathy is central to sociological thinking. As such, fostering empathy in students is a common course goal. In this article, we report the initial findings of a semester-long assessment of empathy change in undergraduate students (N = 619). We employ a mixed-methods research design that utilizes qualitative instructor data to determine independent instructor-level variables and student surveys to measure student empathy change.
  10. Teaching about Learning: The Effects of Instruction on Metacognition in a Sociological Theory Course

    This article investigates the effects of teaching about metacognition in a sociological theory course. I created a series of teaching interventions to introduce students to the science of learning, including an interactive lecture on metacognition, a discussion that models metacognitive strategies, and activities for students to practice metacognition. This article describes those teaching interventions and assesses whether direct instruction led to greater use of metacognitive and cognitive strategies, confidence, and motivation to learn.