Bridging Alone: Religious Conservatism, Marital Homogamy, and Voluntary Association Membership

This study characterizes social insularity of religiously conservative American married couples by examining patterns of voluntary associationmembership. Constructing a dataset of 3938 marital dyads from the second wave of the National Survey of Families and Households, the author investigates whether conservative religious homogamy encourages membership in religious voluntary groups and discourages membership in secular voluntary groups. Results indicate that couples’ shared affiliation with conservative denominations, paired with beliefs in biblical authority and inerrancy, increases the likelihood of religious group membership for husbands and wives and reduces the likelihood of secular group membership for wives, but not for husbands. The social insularity of conservative religious groups appears to be reinforced by homogamy—particularly by wives who share faith with husbands

American Indian and Alaska Native Populations: Envisioning the Future

Historically-based structural disadvantages impinge on AIAN people’s civil rights, and redressing these issues requires plausible information about the future size, age structure, and locational distribution of the population. AIAN people and Tribal Nations are also subject to statistical racism, in which their data (and thus their successes and needs) are ignored because they are relatively small populations. This report presents population projections of the racially-identified American Indian and Alaska Native population from the present to 2050 using a traditional demographic method that has been modified to account for net response change – one of the most significant data-related challenges

What Motivates Mixed Heritage People to Assert Their Ancestries?

Research on mixed heritage people has often focused on their reported race(s) and what these self-reports may reveal about their racial leanings. In the U.S., people are also asked: “What is this person’s ancestry or ethnic origin?” as a census fill-in-the-blank question. Existing research has analyzed the census data on race and ancestry and has uncovered meanings about ethnicity among White Americans, but little is known about the importance of ancestry in the case of mixed heritage people. In this paper, we draw on our interviews with 68 American-Indian-White, Black-White, and Asian-White mixed heritage people in the U.S. Given that many mixed heritage people’s connections with their disparate ancestries can be hindered by generational distance, lack of cultural contact and exposure, and social rejection, what motivates mixed heritage people to report their disparate ancestries, and how do their ancestry claims relate to their racial identities? How may the differential histories and racialization of groups in the U.S. shape mixed heritage people’s ability and inclination to assert either their White or minority ancestries? We found that mixed heritage individuals who were motivated to assert their ancestry claims did so for two main reasons: First, by claiming a specific ancestry (or ancestries), participants wished to assert a more individualistic sense of self than was typically allowed, given their racial treatment based upon their racial appearance; this could be especially meaningful if those individuals felt a mismatch between their racial assignment by others and their sense of self. Second, a claim to a specific ancestry was a way for individuals to forge connections with family, relatives, or an ancestry group that had not existed before. Overall, while mmost of our mixed heritage participants reported details of their European ancestries, it was their Black, American Indian, or Asian ancestries that were deemed to be most salient and/or meaningful to who they were

Friends, Neighbors, and Coworkers at Midlife

with Friends, Neighbors, and Coworkers at Midlife People have always relied on their friends, neighbors, and coworkers as well as family members for social support, but support from outside the family may be increasingly important as high divorce rates persist and high levels of residential mobility continue to take people away from their relatives. Past research suggests that women give and receive more emotional support than do men, but little research has explored gender differences in overall patterns of exchanging social support. We use latent class analysis of data from the Wisconsin Longitudinal Study to show that there are four major patterns of social support exchange for both men and women at midlife. Three of these patterns—high exchange, emotional support exchange, and low exchange—are very similar for men and women. However, almost half of men can be characterized as low exchangers while almost half of women can be characterized as emotional support exchangers. Around 10 percent of both men and women are high exchangers. Multivariate analyses show that among both men and women, the unmarried are the most likely to be high exchangers after controlling for other factors that might possibly be related to th

An outside view: What do observers say about others’ races and Hispanic origins?

Outsiders’ views of a person’s race or Hispanic origin can impact how she sees herself, how she reports her race and Hispanic origins, and her social and economic experiences. The way outsiders describe non-strangers in terms of their race and Hispanic origin may reveal popular assumptions about which race/Hispanic categories are salient for Americans, which kinds of people are seen as multiracial, and the types of cues people use when identifying another person’s race. We study patterns of observer identification using a unique, large, linked data source with two measures of a person’s race and Hispanic origin. One measure (from Census 2000 or the 2010 Census) was provided by a household respondent and the other (from the other census year) was provided by a census proxy reporter (e.g., a neighbor) who responded on behalf of a non-responsive household. We ask: Does an outsider’s report of a person’s race and Hispanic origin match a household report? We find that in about 90% of our 3.7 million (nonrepresentative) cases, proxy reports of a person’s race and Hispanic origin match responses given by the household in a different census year. Match rates are high for the largest groups: non-Hispanic whites, blacks, and Asians and for Hispanics, though proxies are not very able to replicate the race responses of Hispanics. Matches are much less common for people in smaller groups (American Indian/Alaska Native, Pacific Islander, Some Other Race, and multiracial). We also ask: What predicts a matched response and what predicts a particular unmatched response? We find evidence of the persistence of hypodescent for blacks and hyperdescent for American Indians. Biracial Asian-whites and Pacific Islander-whites are more often seen by others as non-Hispanic white than as people of color. Proxy reporters tend to identify children as multiple race and elders as single race, whether they are or not. The race/Hispanic composition of the tract is more powerfully predictive of a particular unmatched response than are tract-level measures of socioeconomic status; unmatched responses are often consistent with the race/Hispanic characteristics of the neighborhood

Occupational Dissimilarity between the American Indian/Alaska Native and the White Workforce in the Contemporary United States

Who has which job? When this answer differs by race group or sex, inefficiencies such as labor market discrimination or suboptimal investment in education may be impeding productivity and sustaining inequities. We use US Census data to analyze the occupational structure of American Indian/Alaska Native (AI/AN) workers relative to non-Hispanic white workers. Relative to white workers, AI/AN workers are generally overrepresented in low-skilled occupations and underrepresented in high-skilled occupations, especially men and single-race AI/AN workers. AI/AN occupational dissimilarity does not appear to have declined substantially since 1980. Sex-specific multivariate analyses do not remove the significant inequalities in observed occupational outcomes

America's Churning Races: Race and Ethnic Response Changes between Census 2000 and the 2010 Census

Race and ethnicity responses can change over time and across contexts – a component of population change not usually taken into account. To what extent do race and/or Hispanic origin responses change? Is change more common to/from some race/ethnic groups than others? Does the propensity to change responses vary by characteristics of the individual? To what extent do these changes affect researchers? We use internal Census Bureau data from the 2000 and 2010 censuses in which individuals’ responses have been linked across years. Approximately 9.8 million people (about 6 percent) in our large, non-representative linked data have a different race and/or Hispanic origin response in 2010 than they did in 2000. Several groups experienced considerable fluidity in racial identification: American Indians and Alaska Natives, Native Hawaiians and Other Pacific Islanders, and multiple-race response groups, as well as Hispanics when reporting a race. In contrast, race and ethnic responses for single-race non-Hispanic whites, blacks, and Asians were relatively consistent over the decade, as were ethnicity responses by Hispanics. People who change their race and/or Hispanic origin response(s) are doing so in a wide variety of ways, as anticipated by previous research. For example, people’s responses change from multiple races to a single race, from a single race to multiple races, from one single race to another, and some people add or drop a Hispanic response. The inflow of people to each race/Hispanic group is in many cases similar in size to the outflow from the same group, such that cross-sectional data would show a small net change. We find response changes across ages, sexes, regions, and response modes, with variation across groups. Researchers should consider the implications of changing race and Hispanic origin responses when conducting analyses and interpreting results