Local Getis-Ord Gi* statistics were calculated as a measure of residential racial segregation. Measures were calculated at the census tract level on the proportion of non-Hispanic White, non-Hispanic Black, non-Hispanic Asian [and Pacific Islander for 1990 and 2000 census], and Hispanic persons per census tract. Gi* statistics are Z-scores that compare the proportion of the population in the focal tract and its neighboring tracts, to the average proportion of a larger geographic unit. For the majority of tracts, the larger geographic unit was the Core-Based Statistical Area (CBSA) these tracts belonged to, and for the minority of tracts that fell outside the boundaries of a CBSA, the County was used as the larger unit.Data for the measures were obtained from the IPUMS National Historical Geographic Information System (NHGIS) data finder. Data were downloaded for the 1990 and 2000 census, and the 2006-2009, 2010-2014, and 2015-2019 5-year American Community Survey (ACS) estimates. Geographically standardized time series tables were used for 1990 and 2000 census data. All other ACS data were standardized to 2010 census tract boundaries.G*statistics were calculated using both Rook and Queen conceptualization of spatial relationships. With Rook contiguity, neighbors are determined by those that share a common edge only, while Queen contiguity neighbors are those that share both an edge or a "corner" (common vertex). See detailed documentation for further details.

Local Getis-Ord Gi* statistics were calculated as a measure of residential segregation. Measures were calculated at the census tract level based on the proportion of non-Hispanic White, non-Hispanic Black, non-Hispanic Asian [and Pacific Islander for 1990 and 2000 census], Hispanic, and immigrant persons (regardless of country of origin; 2008-2012 only) per census tract. Gi* statistics are Z-scores that compare the proportion of the population in the focal tract and its neighboring tracts to the average proportion of a larger geographic unit. For the majority of tracts, the larger geographic unit was the Core-Based Statistical Area (CBSA) these tracts belonged to. The county was used as the larger unit for tracts that fell outside the boundaries of a CBSA.Data for the measures were obtained from the IPUMS National Historical Geographic Information System (NHGIS) data finder. Data were downloaded for the 1990 and 2000 census, and the 2006-2009, 2008-2012 (Immigrant segregation only), 2010-2014, and 2015-2019 5-year American Community Survey (ACS) estimates. Geographically standardized time series tables were used for 1990 and 2000 census data. All other ACS data were standardized to 2010 census tract boundaries.G*statistics were calculated using both Rook and Queen conceptualization of spatial relationships. With Rook contiguity, neighbors are determined by those that share a common edge only, while Queen contiguity neighbors are those that share both an edge or a "corner" (common vertex). See detailed documentation for further details.

The concept of Racially Concentrated Areas of Affluence (RCAAs) was originally developed by scholars at the University of Minnesota to illustrate the flip side of the Racially and Ethnically Concentrated Areas of Poverty (R/ECAPs) metric used by HUD in the 2015 AFFH rule and to more fully tell the story of segregation in the United States. As stated in HCD's AFFH Guidance Memo, when analyzing patterns and trends of segregation and proposing policy approaches in the Housing Element, localities should not only focus on communities of color. Segregation is a continuum, with polarity between race, poverty, and affluence, which can be a direct product of the same policies and practices. To better evaluate these conditions, both sides of the continuum should be considered and compare patterns within the community and across the region. This more holistic approach will better unveil deeply rooted policies and practices and improve identification and prioritization of contributing factors to inform more meaningful actions.HCD has created a new version of the RCAA metric to better reflect California's relative diversity and regional conditions, and to aid local jurisdictions in their analysis of racially concentrated areas of poverty and affluence pursuant to AB 686 and AB 1304. HCD's RCAA metric is provided as a resource to be paired with local data and knowledge - jurisdictions are encouraged but not required to use the RCAA layer provided by HCD in their housing element analyses.To develop the RCAA layer, staff first calculated a Location Quotient (LQ) for each California census tract using data from the 2015-2019 ACS. This LQ represents the percentage of total white population (White Alone, Not Hispanic or Latino) for each census tract compared to the average percentage of total white population for all census tracts in a given COG region. For example, a census tract with a LQ of 1.5 has a percentage of total white population that is 1.5 times higher than the average percentage of total white population in the given COG region.To determine the RCAAs, census tracts with a LQ of more than 1.25 and a median income 1.5 times higher than the COG AMI (or 1.5x the State AMI, whichever is lower) were assigned a numeric score of 1 (Is a RCAA). Census tracts that did not meet this criterion were assigned a score of 0 (Not a RCAA).COG AMI was determined by averaging the 2019 ACS established AMI's for each county within the given COG region. 2019 ACS AMI limits can be found here: https://www.census.gov/quickfacts/fact/table/US/PST045219 [census.gov]. State AMI was based on the ACS 2019 California state AMI ($75,235), which can be found here: https://www.census.gov/quickfacts/fact/table/CA/INC110219 [census.gov].Census tracts with a total population of less than 75 people, in which the census tract was also largely contained within a non-urbanized area such as a park, open space, or airport, were not identified as RCAAs.Data Source: American Community Survey (ACS), 2015-2019References:Wilson, William J. (1980). The Declining Significance of Race: Blacks and Changing American Institutions. Chicago: University of Chicago Press.Damiano, T., Hicks, J., & Goetz, E. (2017). Racially Concentrated Areas of Affluence: A Preliminary Investigation.To learn more about R/ECAPs visit: https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/ch4.pdf [huduser.gov]Original data created by HCD, PlaceWorks 2021

In New York City, the population of Chinese Americans has grown faster than that of any other minority racial/ethnic group, and now this community constitutes almost half of all Chinese Americans living in the northeastern United States. Nonetheless, scant research attention has been given to Chinese American ethnic enclaves and little is known about the health status of their residents. This study aims to help address this gap in the literature by: (1) improving our understanding of the spatial settlement of Chinese Americans living in New York City from 2000 to 2016; and (2) assessing associations between a New York City resident's likelihood of living in a Chinese American enclave and their access to health care and perceived health status, two measures of community health. In support of this aim, this study establishes a robust criterion for defining ethnic enclaves at the Census tract level in New York City as the communities of interest in this paper. An ethnic enclave is defined as an area at the Census tract level with high dissimilarity and a spatial cluster of Chinese Americans. The spatial findings were that Chinese Americans in New York City were least segregated from other Asian American residents, somewhat segregated from White residents, and most segregated from Black residents. Also, the population density of Chinese Americans increased since 2000, as reflected by their declining exposure index with other Asian Americans. Results from logistic regression indicated that the probability of living in a Chinese American enclave was negatively associated with positive self-perception of general health and positively associated with delays in receiving health care. For Chinese American residents of New York City, living in an ethnic enclave was also associated with both lower socioeconomic status and poorer community health.

This dataset was created primarily to map and track socioeconomic and demographic variables from the US Census Bureau from year 1940 to year 2010, by decade, within the City of Baltimore's Mayor's Office of Information Technology (MOIT) year 2010 neighborhood boundaries. The socioeconomic and demographic variables include the percent White, percent African American, percent owner occupied homes, percent vacant homes, the percentage of age 25 and older people with a high school education or greater, and the percentage of age 25 and older people with a college education or greater. Percent White and percent African American are also provided for year 1930. Each of the the year 2010 neighborhood boundaries were also attributed with the 1937 Home Owners' Loan Corporation (HOLC) definition of neighborhoods via spatial overlay. HOLC rated neighborhoods as A, B, C, D or Undefined. HOLC categorized the perceived safety and risk of mortgage refinance lending in metropolitan areas using a hierarchical grading scale of A, B, C, and D. A and B areas were considered the safest areas for federal investment due to their newer housing as well as higher earning and racially homogenous households. In contrast, C and D graded areas were viewed to be in a state of inevitable decline, depreciation, and decay, and thus risky for federal investment, due to their older housing stock and racial and ethnic composition. This policy was inherently a racist practice. Places were graded based on who lived there; poor areas with people of color were labeled as lower and less-than. HOLC's 1937 neighborhoods do not cover the entire extent of the year 2010 neighborhood boundaries. The neighborhood boundaries were also augmented to include which of the year 2017 Housing Market Typology (HMT) the 2010 neighborhoods fall within. Finally, the neighborhood boundaries were also augmented to include tree canopy and tree canopy change year 2007 to year 2015.