American Sociological Association

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  1. Expensive Childcare and Short School Days = Lower Maternal Employment and More Time in Childcare? Evidence from the American Time Use Survey

    This study investigates the relationship between maternal employment and state-to-state differences in childcare cost and mean school day length. Pairing state-level measures with an individual-level sample of prime working-age mothers from the American Time Use Survey (2005–2014; n = 37,993), we assess the multilevel and time-varying effects of childcare costs and school day length on maternal full-time and part-time employment and childcare time.
  2. Collective Social Identity: Synthesizing Identity Theory and Social Identity Theory Using Digital Data

    Identity theory (IT) and social identity theory (SIT) are eminent research programs from sociology and psychology, respectively. We test collective identity as a point of convergence between the two programs. Collective identity is a subtheory of SIT that pertains to activist identification. Collective identity maps closely onto identity theory’s group/social identity, which refers to identification with socially situated identity categories. We propose conceptualizing collective identity as a type of group/social identity, integrating activist collectives into the identity theory model.
  3. Transparency and Embodied Action: Turn Organization and Fairness in Complex Institutional Environments

    Institutional settings in which large numbers of participants have the right and in some cases the responsibility to contribute to the proceedings pose particular challenges to the order and allocation of turns. These challenges are organizational, how to enable and order participation between large numbers of people, as well as moral and political—the fair, transparent, and even distribution of access to the floor.
  4. 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.

  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. 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.