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  1. 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.

  2. Getting the Most Out of the U.S. Healthcare System

    Kids with life-threatening illnesses need cutting-edge technology and medical expertise, but families face uneven access and paths to such care.

  3. Jishuku, Altruism, and Expatriate Emotion

    When a devastating earthquake and tsunami hit japan in 2011, the effects were felt by over a million expatriates worldwide.

  4. Elements of Professional Expertise: Understanding Relational and Substantive Expertise through Lawyers' Impact

    Lawyers keep the gates of public justice institutions, particularly through their roles in formal procedures like hearings and trials. Yet, it is not clear what lawyers do in such quintessentially legal settings: conclusions from past research are bedeviled by a lack of clear theory and inconsistencies in research design. Conceptualizing litigation work in terms of professional expertise, I conduct a theoretically grounded synthesis of the findings of extant studies of lawyers’ impact on civil case outcomes.

  5. The Paradox of Generosity: Giving We Receive, Grasping We Lose

    The Paradox of Generosity: Giving We Receive, Grasping We Lose

  6. Civic Stratification and the Exclusion of Undocumented Immigrants from Cross-border Health Care

    This paper proposes a theoretical framework and an empirical example of the relationship between the civic stratification of immigrants in the United States, and their access to healthcare. We use the 2007 Pew Hispanic Center/Robert Wood Johnson Foundation Hispanic Healthcare Survey, a nationally representative survey of U.S. Latinos (N = 2,783 foreign-born respondents) and find that immigrants who are not citizens or legal permanent residents are significantly more likely to be excluded from care in both the United States and across borders.

  7. 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.

  8. Cancer Diagnosis and Mental Health among Older White Adults: Moderating Role for Social Networks?

    Cancer is a life-changing condition for many American seniors, and a growing body of literature is assessing the mental health implications of living with the disease. This article builds from the well-known buffering hypothesis with insights from recent cancer research to investigate whether social networks moderate the association between cancer and mental health for older men and women.

  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.