Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) is a new approach to quantitative intersectional modelling. Along with an outcome of interest, MAIHDA entails the use of two sets of independent variables. These include group demographics such as race, gender, and poverty status as well as strata which are constructs such as Black female poor, Black female wealthy, and White female poor.
View Article and Find Full Text PDFEmpirical evidence points to a persistent Black-White racial gap in police-caused homicides. Some scholarship treats the gap as denoting criminal justice exposure either in terms of involvement in crime or living in a high-crime context. By contrast, health scholarship typically points to the importance of racism including the attitudes, institutional practices, and overall structures that operate to privilege one group over another.
View Article and Find Full Text PDFIn 19th century U.S., European ethnics were considered dark-skinned and working-class.
View Article and Find Full Text PDFThe US has experienced a substantial decline in social trust in recent decades. Surprisingly few studies analyze whether individual-level explanations can account for this decrease. We use three-wave panel data from the General Social Survey (2006-2014) to study the effects of four possible individual-level sources of changes in social trust: job loss, social ties, income, and confidence in political institutions.
View Article and Find Full Text PDFSubtle gender dynamics in the publishing process involving collaboration, peer-review, readership, citation, and media coverage disadvantage women in academia. In this study we consider whether commenting on published work is also gendered. Using all the comments published over a 16-year period in PNAS (N = 869) and Science (N = 481), we find that there is a gender gap in the authorship of comment letters: women are less likely than men to comment on published academic research.
View Article and Find Full Text PDFCan Rev Sociol
February 2020
Several literatures including those focusing on settler colonialism, critical antiracism as well as ethnic studies and sociology more broadly often position racial injustice and genocide as a struggle against whiteness and white supremacy. Here I use my own positionality to illustrate what might be unseen in the current thinking about the meaning of what whiteness entails. Then I propose the preliminary workings of a nonbinary approach to thinking about racial justice and reconciliation that still centers the specific experiences of oppression but that does not also entail blaming a particular group as oppressor.
View Article and Find Full Text PDFMany immigrants experience discrimination. In this paper we consider how discrimination affects their trust. We make a theoretical case for a formal mediation approach to studying the immigration, discrimination, and trust relationship.
View Article and Find Full Text PDFHousework is asymmetrically distributed by gender. This uneven allocation is an important indicator of inequality between women and men. The imbalance is closing, although exactly why remains uncertain.
View Article and Find Full Text PDFCan Rev Sociol
February 2017
At many Canadian universities it is now common to publicly acknowledge Indigenous lands, treaties, and peoples. Yet, this practice has yet to be considered as a subject of scholarly inquiry. How does this practice vary and why? In this paper we describe the content and practice of acknowledgment, linking this content to treaty relationships (or lack thereof).
View Article and Find Full Text PDFProc Natl Acad Sci U S A
March 2016
Although it is generally accepted that political trust is reflective of satisfaction with the performance of the incumbent administration, this is only considered true for White Americans. Because their trust reflects a larger discontent with the political system, Black Americans, it is held, do not respond in the same way in the short term. This argument has yet to be tested with over-time data.
View Article and Find Full Text PDFWe used metropolitan-level data from the 2000 U.S. census to analyze the hypersegregation of four groups from whites: blacks, Hispanics, Asians, and Native Americans.
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