This dataset contains Race/Ethinicty codes. It is used to enter in patient demographics information.

This layer shows the population broken down by race and Hispanic origin. Data is from US Census American Community Survey (ACS) 5-year estimates.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2018-2022ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table was downloaded and joined with Zip Code boundaries in the City of Tempe.Date of Census update: December 15, 2023National Figures: data.census.gov

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

This layer shows population broken down by race and Hispanic origin. Data is from US Census American Community Survey (ACS) 5-year estimates.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2016-2020ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table downloaded and joined with Zip Code boundaries in the City of Tempe.Date of Census update: March 17, 2022National Figures: data.census.gov

Comparing NHS England SNOMED code mapping with how individuals self-identified their ethnicity in Census 2021.

This dataset includes race/ethnicity of newly Medi-Cal eligible individuals who identified their race/ethnicity as Hispanic, White, Other Asian or Pacific Islander, Black, Chinese, Filipino, Vietnamese, Asian Indian, Korean, Alaskan Native or American Indian, Japanese, Cambodian, Samoan, Laotian, Hawaiian, Guamanian, Amerasian, or Other, by reporting period. The race/ethnicity data is from the Medi-Cal Eligibility Data System (MEDS) and includes eligible individuals without prior Medi-Cal Eligibility. This dataset is part of the public reporting requirements set forth in California Welfare and Institutions Code 14102.5.

This Zenodo entry details the methodology for extracting and reconciling ethnicity data from the Clinical Practice Research Datalink (CPRD), incorporating both General Practitioner (GP) and Hospital Episode Statistics (HES) sources. The approach aims to resolve discrepancies between these sources and provide a standardized single ethnicity value per patient, categorized into 6 and 12 levels according to NHS coding guidelines. Materials and Methods: Ethnicity data from the CPRD are recorded in multiple formats. This study harmonizes these data to achieve consistent ethnicity classification across patient records, following a hierarchal reconciliation protocol prioritizing hospital data over GP records. Ethnicity Levels: Ethnicity data are processed to conform to two levels of granularity: Six high-level categories: White, Black, Asian, Mixed, Other, Unknown Twelve detailed categories: Bangladeshi, Black African, Black Caribbean, Black Other, Chinese, Indian, Mixed, Other Asian, Other, Pakistani, Unknown, White Source Data Mapping: CPRD Medcodes: Directly mapped to 490 SNOMED codes SNOMED to NHS Codes: SNOMED codes are linked to 26 NHS ethnicity codes NHS to HES Codes: These NHS codes further map into 12 HES hospital ethnicities, which then consolidate into the 6 broad categories mentioned above Algorithm (AIM-CISC): Hospital Data Priority: Ethnicity records from hospital sources override those from GP records unless the hospital data is classified as "Unknown", null, or empty. Conflict Resolution Within GP Data: The frequency of recorded ethnicities determines the selection. The most frequently recorded ethnicity prevails. If frequencies are tied, the most recent record is used. In cases where records are equally recent, the first alphabetically listed ethnicity is selected. Unique Patient Identifiers: Each patient is represented once in hospital data, ensuring a single source of truth for hospital-based ethnicities. This simplifies reconciliation with GP data when discrepancies arise. Source Documentation and References: Reference for Code Lists: Digital ethnicity data in population-wide electronic health records in England: a description of completeness, coverage, and granularity of diversity (Pineda-Moncusí et al., 2022): https://doi.org/10.1101/2022.11.11.22282217 GitHub Repository for Code Lists: https://github.com/BHFDSC/CCU037_01/blob/main/england/phenotypes/snomed_meaning_and_map_to_primary_code.csv NHS Ethnicity Codes Documentation: https://www.datadictionary.nhs.uk/attributes/ethnic_category_code_2001.html open_in_new Notes on mapping: Instances were noted where multiple Medcodes map back to a single SNOMED code, highlighting the importance of careful data cross-referencing. For example, two different Medcodes represent the New Zealand European ethnicity, which both map back to the identical SNOMED code.

This layer shows the population broken down by race and Hispanic origin. Data is from US Census American Community Survey (ACS) 5-year estimates.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online). A ‘Null’ entry in the estimate indicates that data for this geographic area cannot be displayed because the number of sample cases is too small (per the U.S. Census).Vintage: 2019-2023ACS Table(s): B03002 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Data Preparation: Data table was downloaded and joined with Zip Code boundaries in the City of Tempe.Date of Census update: December 12, 2024National Figures: data.census.gov

A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco.

The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person.

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco.

When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons:

• The person was not asked about their race and ethnicity.
• The person was asked, but refused to answer.
• The person answered, but the testing provider did not include the person's answers in the reports.
• The testing provider reported the person's answers in a format that could not be used by the health department.

For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.”

B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown."

The Race/Ethnicity categorization increases data clarity by emulating the methodology used by the U.S. Census in the American Community Survey. Specifically, persons who identify as "Asian," "Black or African American," "American Indian or Alaska Native," "Native Hawaiian or Other Pacific Islander," "White," "Multi-racial," or "Other" do NOT include any person who identified as Hispanic/Latino at any time in their testing reports that either (1) identified them as SF residents or (2) as someone who tested without a locating address by an SF provider. All persons across all races who identify as Hispanic/Latino are recorded as “"Hispanic or Latino/a, all races." This categorization increases data accuracy by correcting the way “Other” persons were counted. Previously, when a person reported “Other” for Race/Ethnicity, they would be recorded “Unknown.” Under the new categorization, they are counted as “Other” and are distinct from “Unknown.”

If a person records their race/ethnicity as “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other” for their first COVID-19 test, then this data will not change—even if a different race/ethnicity is reported for this person for any future COVID-19 test. There are two exceptions to this rule. The first exception is if a person’s race/ethnicity value i

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

The EEO Tabulation is sponsored by four Federal agencies consisting of the Equal Employment Opportunity Commission (EEOC), the Employment Litigation Section of the Civil Rights Division at the Department of Justice (DOJ), the Office of Federal Contract Compliance Programs (OFCCP), and the Office of Personnel Management (OPM), and developed in conjunction with the U.S. Census Bureau..Supporting documentation on code lists and subject definitions can be found on the Equal Employment Opportunity Tabulation website. https://www.census.gov/topics/employment/equal-employment-opportunity-tabulation.html.Source: U.S. Census Bureau, 2014-2018 American Community Survey.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see https://www.census.gov/programs-surveys/acs/technical-documentation.html The effect of nonsampling error is not represented in these tables)..The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB). Except for the total, all race and ethnicity categories are mutually exclusive. "Black" refers to Black or African American; "AIAN" refers to American Indian and Alaska Native; and "NHPI" refers to Native Hawaiian and Other Pacific Islander. "Balance of Not Hispanic or Latino" includes the balance of non-Hispanic individuals who reported multiple races or reported Some Other Race alone. For more information on race and Hispanic origin, see the Subject Definitions at https://www.census.gov/programs-surveys/acs/technical-documentation.html..Race and Hispanic origin are separate concepts on the American Community Survey. "White alone Hispanic or Latino" includes respondents who reported Hispanic or Latino origin and reported race as "White" and no other race. "All other Hispanic or Latino" includes respondents who reported Hispanic or Latino origin and reported a race other than "White," either alone or in combination..Occupation titles and their 4-digit codes are based on the 2018 Standard Occupational Classification..The 2014-2018 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Explanation of Symbols:An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the median itself.An "(X)" means that the estimate is not applicable or not available.An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "***" entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate.An "*****" entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate.An "N" entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small.An "-" following a median estimate means the median falls in the lowest interval of an open-ended distribution.An "+" following a median estimate means the median falls in the upper interval of an open-ended distribution.

Table contains count and percent distribution of county residents by racial/ethnic categories. Data are summarized at county, city, zip code and census tract of residence. Data are presented for zip codes (ZCTAs) fully within the county. People of color category includes people who identify as Latino, African American, American Indian/Alaska Native, Asian, Pacific Islander, or multi-race. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B03002; data accessed on April 11, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (String): Geography IDNAME (String): Name of geographyt_pop (Numeric): Total populationAfrican_American_NH (Numeric): Number of non-Hispanic African Americansp_African_American_NH (Numeric): Percent of non-Hispanic African AmericansAsian_NH (Numeric): Number of non-Hispanic Asiansp_Asian_NH (Numeric): Percent of non-Hispanic AsiansLatino (Numeric): Number of Latinosp_Latino (Numeric): Percent of LatinosWhite_NH (Numeric): Number of non-Hispanic Whitep_White_NH (Numeric): Percent of non-Hispanic Whitepeople_of_color2 (Numeric): Number of people of colorp_poc2 (Numeric): Percent of people of color

Excel workbook containing code listings for Diabetes and Infection study.

It consists of the following datasheets

Read and SNOMED CT codes for a diagnosis of pre-diabetes Read and SNOMED CT Codes for a test result indicative of pre-diabetes
Read and SNOMED CT codes for a diagnosis of type 2 diabetes Read and SNOMED CT codes for a diagnosis of type 1 diabetes Read and SNOMED CT codes for a non-specific diagnosis of diabetes Read and SNOMED CT codes for primary care infections ICD-10 Codes for hospital infections

Table from the American Community Survey (ACS) 5-year series on race and ethnicity related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B03002 Hispanic or Latino Origin by Race, B02008-B02013 Race Alone or in Combination with One or More. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.

Ethnic codes as defined by the Health Management Information System.

About this dataset

Context

The dataset tabulates the population of Baldwin by race. It includes the population of Baldwin across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Baldwin across relevant racial categories.

Key observations

The percent distribution of Baldwin population by race (across all racial categories recognized by the U.S. Census Bureau): 80.75% are white, 4.13% are Black or African American, 0.03% are American Indian and Alaska Native, 8.60% are Asian, 2.56% are some other race and 3.94% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Baldwin
• Population: The population of the racial category (excluding ethnicity) in the Baldwin is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Baldwin total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Baldwin Population by Race & Ethnicity. You can refer the same here

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Since the 5-year data do not benefit from data quality filtering, comparisons are only made for populations of 5,000 or more..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..An * indicates that the estimate is significantly different (at a 90% confidence level) than the estimate from the most current year. A "c" indicates the estimates for that year and the current year are both controlled; a statistical test is not appropriate. A blank indicates that the estimate is not significantly different from the estimate of the most current year, or that a test could not be done because one or both of the estimates is displayed as "-", "N", or "(X)", or the estimate ends with a "+" or "-". (For more information on these symbols, see the Explanation of Symbols.).Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A mar...

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..For more information on understanding Hispanic origin and race data, please see the America Counts: Stories Behind the Numbers article entitled, 2020 Census Illuminates Racial and Ethnic Composition of the Country, issued August 2021..The Hispanic origin and race codes were updated in 2020. For more information on the Hispanic origin and race code changes, please visit the American Community Survey Technical Documentation website..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER data base. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on January 1, 2000 legal boundaries. A complete set of Redistricting Census 2000 TIGER/Line files includes all counties and statistically equivalent entities in the United States and Puerto Rico. The Redistricting Census 2000 TIGER/Line files will not include files for the Island Areas. The Census TIGER data base represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The Redistricting Census 2000 TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. The Redistricting Census 2000 TIGER/Line files do NOT contain the ZIP Code Tabulation Areas (ZCTAs) and the address ranges are of approximately the same vintage as those appearing in the 1999 TIGER/Line files. That is, the Census Bureau is producing the Redistricting Census 2000 TIGER/Line files in advance of the computer processing that will ensure that the address ranges in the TIGER/Line files agree with the final Master Address File (MAF) used for tabulating Census 2000. The files contain information distributed over a series of record types for the spatial objects of a county. There are 17 record types, including the basic data record, the shape coordinate points, and geographic codes that can be used with appropriate software to prepare maps. Other geographic information contained in the files includes attributes such as feature identifiers/census feature class codes (CFCC) used to differentiate feature types, address ranges and ZIP Codes, codes for legal and statistical entities, latitude/longitude coordinates of linear and point features, landmark point features, area landmarks, key geographic features, and area boundaries. The Redistricting Census 2000 TIGER/Line data dictionary contains a complete list of all the fields in the 17 record types.

All R code for replicating the tables, results, and graphs in "Representing Race and Ethnicity in American Fiction". Code is separated into three different files for a) deriving distinctive collocates from a set of text files, b) creating t-sne visualizations of high dimensional word cooccurrence data, and c) assessing internal and external coherence of collocates based on assigned targets and groups. Also included is the complete list of collocates for both the Gale American Fiction corpus as a whole, as well as the same corpus divided into 25 year windows. The original target list can be found embedded in these tables (which show the strength of association between collocate and target). PLEASE NOTE CONTENT WARNING: while the text of the paper has been edited to remove offensive and harmful language, we present the background data for replication purposes "as-is" based on the language of the original novels themselves