Support for the Ecological Framework for Understanding Multiracial Identity using Latent Profile Analysis

The current study presents a statistical model of the roles of racial identity, racial identification, and racial category under the ecological framework for understanding multiracial identity. The purposes of this study were threefold: (1) to identify distinct profiles of how multiracials understand their racial identity using latent profile analysis; (2) to investigate whether racial identification variables predicted profile membership; and (3) to examine whether profile membership differentiated multiracials across racial category and adjustment outcomes. Using a sample of 269 multiracial adults (77% female, Mage = 23.10) recruited from a southwestern university in 2018, we identified three profiles of racial identity orientations: Singular-oriented (9%; n = 23), Border-oriented (45%; n = 120), and Protean-oriented (47%; n = 126). The Singular-oriented profile was characterized by the highest level of racial distance, and the lowest levels of multiracial pride, challenges with racial identity, and creating a third space. The Border-oriented profile was characterized by the lowest level of racial distance, and the highest level of multiracial pride. The Protean-oriented profile was characterized by the highest levels of racial conflict, challenges with racial identity, and shifting racial expressions. Several racial identification variables significantly predicted profile membership, including gender, Black racial heritage, and perceived racial ambiguity. Furthermore, the three racial identity profiles predicted variation in racial typology choices, proximity to whiteness, distress, collective efficacy, and sense of belonging. These findings attest to the importance of using person-centered techniques to empirically support the ecological framework for understanding multiracial identity.

On the Mis-Education of Teachers of Color: A Letter to Teacher Educators

Although teacher education researchers have long claimed their commitment to successfully preparing teachers to educate students of Color—a growing majority in U.S. schools—notably absent from their attempts are the voices of teachers of Color. This silence often results in pathological portrayals, positioning teachers of Color as the problem while obscuring the pervasive, problematic, and harmful Whiteness of teaching and teacher education. In this context, inspired by James Baldwin’s letter-essays and centering truthtelling as theoretical framework, eight tenured New York City public school teachers of Color and a teacher educator of Color engaged in collective analysis of a truthtelling exercise focused on what practitioners and institutions of teacher education can and should learn from teachers of Color to develop an antidote to the overwhelming Whiteness of teaching and teacher education, which has been shown to disproportionately disadvantage students of Color. Herein, we offer a composite counter-story—a letter to White teacher educators and, in fact, teacher educators of any racial identification who are in any way aligned with protecting and upholding Whiteness—revisiting our own nuanced memories of becoming and being teachers, unveiling teacher education’s epistemic violence, and issuing a call to action.

Minmaxing of Bayesian Improved Surname Geocoding and Geography Level Ups in Predicting Race

Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian improved surname geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the level of geography used in this process varies widely. Whereas some existing work makes use of geocoding to place individuals in precise census blocks, a substantial portion either skips geocoding altogether or relies on estimation using surname or county-level analyses. Presently, the trade-offs of such variation are unknown. In this letter, we quantify those trade-offs through a validation of BISG on Georgia’s voter file using both geocoded and nongeocoded processes and introduce a new level of geography—ZIP codes—to this method. We find that when estimating the racial identification of White and Black voters, nongeocoded ZIP code-based estimates are acceptable alternatives. However, census blocks provide the most accurate estimations when imputing racial identification for Asian and Hispanic voters. Our results document the most efficient means to sequentially conduct BISG analysis to maximize racial identification estimation while simultaneously minimizing data missingness and bias.

Shifts in Racial Self-Identification for the Greatest Generation: Evidence from Social Security Administrative Data

Researchers generally recognize that racial identification may shift over the life course. However, there is less consensus about the prevalence of these shifts. Previous estimates suggest as many as 6% of Americans shift their racial identity. Using administrative data on Social Security applications from 1984 to 2007, we quantify the magnitude and direction of shifts in racial and ethnic self-identification among Black, White, Asian, American Indian, and Hispanic members of the “Greatest Generation,” those born between 1901 and 1927 (N = 410,388). Approximately 9,274 (2.3%) persons in this dataset changed their racial or Hispanic identity, with distinct patterns of change for racial-ethnic subgroups. Overall, the most common shift was from a non-White identity to a non-Hispanic White identity. We then link to the 1940 Census to investigate whether social status in youth and young adulthood predicts a shift in identity in later life, and we find a positive and significant association between socioeconomic status in early life and a shift from non-White to non-Hispanic White identity. These systematic patterns would be unlikely if these shifts were due entirely to measurement error. We conclude the prevalence of racial fluidity is itself contingent, varying across time and cohort with response to racial climate, events in greater society, and social position.

Gender, Generation, and Multiracial Identification in the United States

Multiracial self-identification is frequently portrayed as a disproportionately female tendency, but previous research has not probed the conditions under which this relationship might occur. Using the 2015 Pew Survey of Multiracial Adults, we offer a more comprehensive analysis that considers gender differences at two distinct stages: reporting multiple races in one's ancestry and selecting multiple races to describe oneself. We also examine self-identification patterns by the generational locus of multiracial ancestry. We find that females are more likely to be aware of multiracial ancestry overall, but only first-generation females are more likely than their male counterparts to self-identify as multiracial. Finally, we explore the role of racial ancestry combination, finding that multiracial awareness and self-identification are likely gendered differently for different segments of the mixed-race population. This offers a more nuanced picture of how gender interacts with other social processes to shape racial identification in the United States.

Hiroshima/Vietnam/Tule Lake

The origin of Asian American political identity was not in cultural nationalism but in diasporic consciousness, most notably in the concept of solidarity with Third World peoples struggling against imperialism around the globe. The poetry of Janice Mirikitani juxtaposes locations from Vietnam to Zimbabwe to the Tule Lake internment camp, making transnational political solidarity prior to, not dependent upon, racial identification. In contrast, the anthology Aiiieeeee!, often cited as the origin of Asian American literary politics, emphasizes the integrity of the individual writer over communal identification. Restoring Mirikitani’s place in the history of Asian American literature also restores a coalitional, transnational vision of Asian American politics that lays the groundwork for a contemporary poetics of the Asian diaspora.

Measuring Race and Ancestry in the Age of Genetic Testing

Will the rise of genetic ancestry tests (GATs) change how Americans respond to questions about race and ancestry on censuses and surveys? To provide an answer, we draw on a unique study of more than 100,000 U.S. adults that inquired about respondents' race, ancestry, and genealogical knowledge. We find that people in our sample who have taken a GAT, compared with those who have not, are more likely to self-identify as multiracial and are particularly likely to select three or more races. This difference in multiple-race reporting stems from three factors: (1) people who identify as multiracial are more likely to take GATs; (2) GAT takers are more likely to report multiple regions of ancestral origin; and (3) GAT takers more frequently translate reported ancestral diversity into multiracial self-identification. Our results imply that Americans will select three or more races at higher rates in future demographic data collection, with marked increases in multiple-race reporting among middle-aged adults. We also present experimental evidence that asking questions about ancestry before racial identification moderates some of these GAT-linked reporting differences. Demographers should consider how the meaning of U.S. race data may be changing as more Americans are exposed to information from GATs.