American Sociological Association

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  1. Neoliberalism

    Johanna Bockman unpacks a hefty term, neoliberalism. She cites its roots and its uses, decoding it as a description of a “bootstraps” ideology that trumpets individualism and opportunity but enforces conformity and ignores structural constraints.

  2. Rethinking Crime and Immigration

    The summer of 2007 witnessed a perfect storm of controversy over immigration to the United States. After building for months with angry debate, a widely touted immigration reform bill supported by President George W. Bush and many leaders in Congress failed decisively. Recriminations soon followed across the political spectrum.

  3. Seeing Disorder: Neighborhood Stigma and the Social Construction of “Broken Windows”

    This article reveals the grounds on which individuals form perceptions of disorder. Integrating ideas about implicit bias and statistical discrimination with a theoretical framework on neighborhood racial stigma, our empirical test brings together personal interviews, census data, police records, and systematic social observations situated within some 500 block groups in Chicago. Observed disorder predicts perceived disorder, but racial and economic context matter more.

  4. Frame-Induced Group Polarization in Small Discussion Networks

    We present a novel explanation for the group polarization effect whereby discussion among like-minded individuals induces shifts toward the extreme. Our theory distinguishes between a quantitative policy under debate and the discussion’s rhetorical frame, such as the likelihood of an outcome. If policy and frame position are mathematically related so that frame position increases more slowly as the policy becomes more extreme, majority formation at the extreme is favored, thereby shifting consensus formation toward the extreme.
  5. The Spatial Proximity and Connectivity Method for Measuring and Analyzing Residential Segregation

    In recent years, there has been increasing attention focused on the spatial dimensions of residential segregation—from the spatial arrangement of segregated neighborhoods to the geographic scale or relative size of segregated areas. However, the methods used to measure segregation do not incorporate features of the built environment, such as the road connectivity between locations or the physical barriers that divide groups. This paper introduces the spatial proximity and connectivity (SPC) method for measuring and analyzing segregation.
  6. Estimating Income Statistics from Grouped Data: Mean-constrained Integration over Brackets

    Researchers studying income inequality, economic segregation, and other subjects must often rely on grouped data—that is, data in which thousands or millions of observations have been reduced to counts of units by specified income brackets.
  7. Deciding on the Starting Number of Classes of a Latent Class Tree

    In recent studies, latent class tree (LCT) modeling has been proposed as a convenient alternative to standard latent class (LC) analysis. Instead of using an estimation method in which all classes are formed simultaneously given the specified number of classes, in LCT analysis a hierarchical structure of mutually linked classes is obtained by sequentially splitting classes into two subclasses. The resulting tree structure gives a clear insight into how the classes are formed and how solutions with different numbers of classes are substantively linked to one another.
  8. Nonlinear Autoregressive Latent Trajectory Models

    Autoregressive latent trajectory (ALT) models combine features of latent growth curve models and autoregressive models into a single modeling framework. The development of ALT models has focused primarily on models with linear growth components, but some social processes follow nonlinear trajectories. Although it is straightforward to extend ALT models to allow for some forms of nonlinear trajectories, the identification status of such models, approaches to comparing them with alternative models, and the interpretation of parameters have not been systematically assessed.
  9. Causal Inference with Networked Treatment Diffusion

    Treatment interference (i.e., one unit’s potential outcomes depend on other units’ treatment) is prevalent in social settings. Ignoring treatment interference can lead to biased estimates of treatment effects and incorrect statistical inferences. Some recent studies have started to incorporate treatment interference into causal inference. But treatment interference is often assumed to follow a simple structure (e.g., treatment interference exists only within groups) or measured in a simplistic way (e.g., only based on the number of treated friends).
  10. Estimating the Relationship between Time-varying Covariates and Trajectories: The Sequence Analysis Multistate Model Procedure

    The relationship between processes and time-varying covariates is of central theoretical interest in addressing many social science research questions. On the one hand, event history analysis (EHA) has been the chosen method to study these kinds of relationships when the outcomes can be meaningfully specified as simple instantaneous events or transitions.