Method: Data for this study are drawn from the Seattle Neighborhoods and Crime Survey. Neighborhood racial preference is measured using four items assessing if an individual is in favor of living in a neighborhood where one-fourth of the neighbors belong to one of four racial/ethnic groups: white, black, Asian, or Hispanic/Latino. Perceived neighborhood racial composition is measured as the proportion of neighbors that are white based on four categories: 1) nearly all, 2) more than half, 3) some, 4) hardly any.
A latent class analysis was conducted to test for patterns of neighborhood racial preference among respondents. A multinomial logistic regression was used to test for predictors of class membership including latent class membership, age, race, gender, marital status, income, and home ownership.
Results: Analyses found four patterns of neighborhood racial preference. The most prevalent class (51.5%, n = 1,468) is labeled “apathetic” because over 90% of respondents stated that they are ‘neutral’ on each of the preferred neighborhood racial composition items. The smallest class (9.5%, n = 270) – is labeled “Discriminatory” because a large proportion of individuals in this class stated that they are either neutral, or somewhat opposed to living in neighborhoods where one-fourth of the individuals are Black or Hispanic.
Another class (18.9% n = 538) is labeled “very much in favor” because most individuals in the class stated that they are very much in favor of living with each racial or ethnic group. The final class (20.1%, n = 575) is labeled “somewhat in favor” because a large proportion of individuals endorsed “somewhat in favor” on the neighborhood racial preference items.
Being very much in favor of neighborhood diversity is associated with greater odds of living in a neighborhood where only some of the neighbors are white (O.R. = 1.356, s.e. = 0.141). Completing college (O.R. = 1.638, s.e. = 0.205) and earning over $75,000 (O.R. = 1.294, s.e. = 0.115) are also associated with greater odds of living in a predominantly white neighborhood.
Conclusions: Results suggest that individuals typically do not live in a diverse neighborhood unless they are very intentional about diversity. This finding is important for addressing segregation. Individuals who purchase their home based on factors that are not explicitly informed by race such as quality schools may contribute to racial and economic segregation by reinforcing the historical, race-based policies that created the gap between schools in lower-income neighborhoods of color and more affluent schools found in predominantly white neighborhoods. Thus, it is important to discuss how seemingly race-neutral decisions today may unintentionally perpetuate racially-biased policies of the past. Further, the findings emphasize the importance of the intentionality of individuals in terms of addressing racial and economic segregation.