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  1. Study Uses 311 Complaints to Track Where and When Neighborhood Conflict Emerges

    Each year, 311 — New York City's main hub for government information and non-emergency services — receives millions of requests and complaints, including New Yorkers' gripes about their neighbors.

  2. Actresses Must Be Picky About With Whom They Work to Survive in Movie Industry

    Actresses need to be pickier than men about with whom they work if they want to survive in the movie industry, suggests a new study.

    "My research indicates that women in the film industry suffer a lack of access to future career opportunities when they tend to work with people who have collaborated frequently in the past," said Mark Lutter, lead author of the study and head of the "Transnational Diffusion of Innovation" Research Group at the Max Planck Institute for the Study of Societies (MPIfG) in Germany.

  3. Shift to Gay, Lesbian, Bisexual Identities in Early Adulthood Tied to Depressive Symptoms

    People whose sexual identities changed toward same-sex attraction in early adulthood reported more symptoms of depression in a nationwide survey than those whose sexual orientations did not change or changed in the opposite direction, according to a new study by a University of Illinois at Chicago (UIC) sociologist.

  4. Lightness/Darkness of Skin Affects Male Immigrants' Likelihood of Gaining Employment

    Skin color is a significant factor in the probability of employment for male immigrants to the United States, according to a new study by two University of Kansas (KU) researchers.

  5. Discrimination in Lending Markets: Status and the Intersections of Gender and Race

    Research documents that lenders discriminate between loan applicants in traditional and peer-to-peer lending markets, yet we lack knowledge about the mechanisms driving lenders’ behavior. I offer one possible mechanism: When lenders assess borrowers, they are implicitly guided by cultural stereotypes about the borrowers’ status. This systematically steers lenders toward funding higher status groups even when applicants have the same financial histories.

  6. The Contingent Value of Embeddedness: Self-affirming Social Environments, Network Density, and Well-being

    Social capital theorists claim that belonging to a densely knit social network creates a shared identity, mutually beneficial exchange, trust, and a sense of belonging in that group. Taken together with the empirical research on the importance of social support and social integration for individuals’ well-being, there is reason to expect that the density of one’s personal social network should be positively related to well-being.

  7. A "Global Interdependence" Approach to Multidimensional Sequence Analysis

    Although sequence analysis has now become a widespread approach in the social sciences, several strategies have been developed to handle the specific issue of multidimensional sequences. These strategies have distinct characteristics related to the way they explicitly emphasize multidimensionality, interdependence, and parsimony.

  8. A Progressive Supervised-learning Approach to Generating Rich Civil Strife Data

    "Big data" in the form of unstructured text pose challenges and opportunities to social scientists committed to advancing research frontiers. Because machine-based and human-centric approaches to content analysis have different strengths for extracting information from unstructured text, the authors argue for a collaborative, hybrid approach that combines their comparative advantages.

  9. A Design and a Model for Investigating the Heterogeneity of Context Effects in Public Opinion Surveys

    Context effects on survey response, caused by the unobserved interaction between beliefs stored in personal memory and triggers generated by the structure of the survey instrument, are a pervasive challenge to survey research. The authors argue that randomized survey experiments on representative samples, when paired with facilitative primes, can enable researchers to model selection into variable context effects, revealing heterogeneity at the population level.

  10. An Introduction to the General Monotone Model with Application to Two Problematic Data Sets

    We argue that the mismatch between data and analytical methods, along with common practices for dealing with "messy" data, can lead to inaccurate conclusions. Specifically, using previously published data on racial bias and culture of honor, we show that manifest effects, and therefore theoretical conclusions, are highly dependent on how researchers decide to handle extreme scores and nonlinearities when data are analyzed with traditional approaches.