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TwitterRace is a social and historical construct, and the racial categories counted by the census change over time so the process of constructing stable racial categories for these 50 years out of census data required complex and imperfect decisions. Here we have used historical research on early 20th century southern California to construct historic racial categories from the IPUMS full count data, which allows us to track groups that were not formally classified as racial groups in some census decades like Mexican, but which were important racial categories in southern California. Detailed explanation of how we constructed these categories and the rationale we used for the decisions we made can be found here. Layers are symbolized to show the percentage of each of the following groups from 1900-1940:AmericanIndian Not-Hispanic, AmericanIndian Hispanic, Black non-Hispanic, Black-Hispanic, Chinese, Korean, Filipino and Japanese, Mexican, Hispanic Not-Mexican, white non-Hispanic. The IPUMS Census data is messy and includes some errors and undercounts, making it hard to map some smaller populations, like Asian Indians (in census called Hindu in 1920) and creating a possible undercount of Native American populations. The race data mapped here also includes categories that may not have been socially meaningful at the time like Black-Hispanic, which generally would represent people from Mexico who the census enumerator classified as Black because of their dark skin, but who were likely simply part of Mexican communities at the time. We have included maps of the Hispanic not-Mexican category which shows very small numbers of non-Mexican Hispanic population, and American Indian Hispanic, which often captures people who would have been listed as Indian in the census, probably because of skin color, but had ancestry from Mexico (or another Hispanic country). This category may include some indigenous Californians who married into or assimilated into Mexican American communities in the early 20th century. If you are interested in mapping some of the other racial or ethnic groups in the early 20th century, you can explore and map the full range of variables we have created in the People's History of the IE IE_ED1900-1940 Race Hispanic Marriage and Age Feature layer.Suggested Citation: Tilton, Jennifer. People's History Race Ethnicity Dot Density Map 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. 2025Feature Layer CitationTilton, Jennifer, Tessa VanRy & Lisa Benvenuti. Race and Demographic Data 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. Additional contributing authors: Mackenzie Nelson, Will Blach & Andy Garcia Funding provided by: People’s History of the IE: Storyscapes of Race, Place, and Queer Space in Southern California with funding from NEH-SSRC Grant 2022-2023 & California State Parks grant to Relevancy & History. Source for Census Data 1900- 1940 Ruggles, Steven, Catherine A. Fitch, Ronald Goeken, J. David Hacker, Matt A. Nelson, Evan Roberts, Megan Schouweiler, and Matthew Sobek. IPUMS Ancestry Full Count Data: Version 3.0 [dataset]. Minneapolis, MN: IPUMS, 2021. Primary Sources for Enumeration District Linework 1900-1940 Steve Morse provided the full list of transcribed EDs for all 5 decades "United States Enumeration District Maps for the Twelfth through the Sixteenth US Censuses, 1900-1940." Images. FamilySearch. https://FamilySearch.org: 9 February 2023. Citing NARA microfilm publication A3378. Washington, D.C.: National Archives and Records Administration, 2003. BLM PLSS Map Additional Historical Sources consulted include: San Bernardino City Annexation GIS Map Redlands City Charter Proposed with Ward boundaries (Not passed) 1902. Courtesy of Redlands City Clerk. Redlands Election Code Precincts 1908, City Ordinances of the City of Redlands, p. 19-22. Courtesy of Redlands City Clerk Riverside City Charter 1907 (for 1910 linework) courtesy of Riverside City Clerk. 1900-1940 Raw Census files for specific EDs, to confirm boundaries when needed, accessed through Family Search. If you have additional questions or comments, please contact jennifer_tilton@redlands.edu.
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TwitterFor the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail.The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts.The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate.More information about these data is available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review FAQs.Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data.Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR).1. Population Density: 2020 Population per square mile,2. Poverty Rate: Percentage of population under 100% FPL,3. Median Household income: Based on countywide median HH income of $71,538.4. Highschool Education Attainment: Percentage of 18 years and older population without high school graduation.5. English Speaking Ability: Percentage of 18 years and older population with less or none English speaking ability. 6. Household without Internet Access: Percentage of HH without internet access.7. Non-Hispanic White Population: Percentage of Non-Hispanic White population.8. Non-Hispanic African-American Population: Percentage of Non-Hispanic African-American population.9. Non-Hispanic Asian Population: Percentage of Non-Hispanic Asian population.10. Hispanic Population: Percentage of Hispanic population.
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TwitterMonaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.
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TwitterThis map shows median age in the US by country, state, county, tract, and congressional district for 2023. ArcGIS Online account required for use.The pop-up is configured to show median age, median age by sex, child age (under 18) population, senior age (over 65) population, the age dependency ratio, and population by 5 year age increments. Blending is used at the Tract level to highlight areas of human settlement. Congressional district is turned off by default and can be enabled in the Layers pane.Esri 2023 Age Dependency Ratio is the estimated ratio of the child population (Age 0-17) and senior population (Age 65+) to the working-age population (Age 18-64) in the geographic area. This ratio is then multiplied by 100. Higher ratios denote that a greater burden is carried by working-age people. Lower ratios mean more people are working who can support the dependent population. Read more. See Updated Demographics for more information on Esri Demographic variables.Esri Updated Demographics represent the suite of annually updated U.S. demographic data that provides current-year and five-year forecasts for more than two thousand demographic and socioeconomic characteristics, a subset of which is included in this layer. Included are a host of tables covering key characteristics of the population, households, housing, age, race, income, and much more. Esri's Updated Demographics data consists of point estimates, representing July 1 of the current and forecast years.Get started with U.S. Updated DemographicsHow to use and interpret U.S. Updated DemographicsEsri Updated Demographics DocumentationMethodologyEssential Esri Demographics vocabularyThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. This layer requires an ArcGIS Online subscription and does not consume credits. Please cite Esri when using this data. For information about purchasing additional Esri's Updated Demographics data, contact datasales@esri.com. Feedback: we would like to hear from you while this layer is in beta release. If you have any feedback regarding this item or Esri Demographics, please use this survey. Fields available:GEOIDNameState NameState Abbreviation2023 Total Population (Esri)2023 Household Population (Esri)2023 Group Quarters Population (Esri)2023 Population Density (Pop per Square Mile) (Esri)2023 Total Households (Esri)2023 Average Household Size (Esri)2023 Total Housing Units (Esri)2023 Owner Occupied Housing Units (Esri)2023 Renter Occupied Housing Units (Esri)2023 Vacant Housing Units (Esri)2020-2023 Population: Compound Annual Growth Rate (Esri)2020-2023 Households: Compound Annual Growth Rate (Esri)2023 Housing Affordability Index (Esri)2023 Percent of Income for Mortgage (Esri)2023 Wealth Index (Esri)2023 Socioeconomic Status Index (Esri)2023 Generation Alpha Population (Born 2017 or Later) (Esri)2023 Generation Z Population (Born 1999 to 2016) (Esri)2023 Millennial Population (Born 1981 to 1998) (Esri)2023 Generation X Population (Born 1965 to 1980) (Esri)2023 Baby Boomer Population (Born 1946 to 1964) (Esri)2023 Silent & Greatest Generations Population (Born 1945/Earlier) (Esri)2023 Population by Generation Base (Esri)2023 Child Population (Age <18) (Esri)2023 Working-Age Population (Age 18-64) (Esri)2023 Senior Population (Age 65+) (Esri)2023 Child Dependency Ratio (Esri)2023 Age Dependency Ratio (Esri)2023 Senior Dependency Ratio (Esri)2023 Total Population Age 0-4 (Esri)2023 Total Population Age 5-9 (Esri)2023 Total Population Age 10-14 (Esri)2023 Total Population Age 15-19 (Esri)2023 Total Population Age 20-24 (Esri)2023 Total Population Age 25-29 (Esri)2023 Total Population Age 30-34 (Esri)2023 Total Population Age 35-39 (Esri)2023 Total Population Age 40-44 (Esri)2023 Total Population Age 45-49 (Esri)2023 Total Population Age 50-54 (Esri)2023 Total Population Age 55-59 (Esri)2023 Total Population Age 60-64 (Esri)2023 Total Population Age 65-69 (Esri)2023 Total Population Age 70-74 (Esri)2023 Total Population Age 75-79 (Esri)2023 Total Population Age 80-84 (Esri)2023 Total Population Age 85+ (Esri)2023 Median Age (Esri)2023 Male Population (Esri)2023 Median Male Age (Esri)2023 Female Population (Esri)2023 Median Female Age (Esri)2023 Total Population by Five-Year Age Base (Esri)2023 Total Daytime Population (Esri)2023 Daytime Population: Workers (Esri)2023 Daytime Population: Residents (Esri)2023 Daytime Population Density (Pop per Square Mile) (Esri)2023 Civilian Population Age 16+ in Labor Force (Esri)2023 Employed Civilian Population Age 16+ (Esri)2023 Unemployed Population Age 16+ (Esri)2023 Unemployment Rate (Esri)2023 Civilian Population 16-24 in Labor Force (Esri)2023 Employed Civilian Population Age 16-24 (Esri)2023 Unemployed Population Age 16-24 (Esri)2023 Unemployment Rate: Population Age 16-24 (Esri)2023 Civilian Population 25-54 in Labor Force (Esri)2023 Employed Civilian Population Age 25-54 (Esri)2023 Unemployed Population Age 25-54 (Esri)2023 Unemployment Rate: Population Age 25-54 (Esri)2023 Civilian Population 55-64 in Labor Force (Esri)2023 Employed Civilian Population Age 55-64 (Esri)2023 Unemployed Population Age 55-64 (Esri)2023 Unemployment Rate: Population Age 55-64 (Esri)2023 Civilian Population 65+ in Labor Force (Esri)2023 Employed Civilian Population Age 65+ (Esri)2023 Unemployed Population Age 65+ (Esri)2023 Unemployment Rate: Population Age 65+ (Esri)2023 Child Economic Dependency Ratio (Esri)2023 Working-Age Economic Dependency Ratio (Esri)2023 Senior Economic Dependency Ratio (Esri)2023 Economic Dependency Ratio (Esri)2023 Hispanic Population (Esri)2023 White Non-Hispanic Population (Esri)2023 Black/African American Non-Hispanic Population (Esri)2023 American Indian/Alaska Native Non-Hispanic Population (Esri)2023 Asian Non-Hispanic Population (Esri)2023 Pacific Islander Non-Hispanic Population (Esri)2023 Other Race Non-Hispanic Population (Esri)2023 Multiple Races Non-Hispanic Population (Esri)2023 Diversity Index (Esri)2023 Population by Race Base (Esri)2023 Population Age 25+: Less than 9th Grade (Esri)2023 Population Age 25+: 9-12th Grade/No Diploma (Esri)2023 Population Age 25+: High School Diploma (Esri)2023 Population Age 25+: GED/Alternative Credential (Esri)2023 Population Age 25+: Some College/No Degree (Esri)2023 Population Age 25+: Associate's Degree (Esri)2023 Population Age 25+: Bachelor's Degree (Esri)2023 Population Age 25+: Graduate/Professional Degree (Esri)2023 Educational Attainment Base (Pop 25+)(Esri)2023 Household Income less than $15,000 (Esri)2023 Household Income $15,000-$24,999 (Esri)2023 Household Income $25,000-$34,999 (Esri)2023 Household Income $35,000-$49,999 (Esri)2023 Household Income $50,000-$74,999 (Esri)2023 Household Income $75,000-$99,999 (Esri)2023 Household Income $100,000-$149,999 (Esri)2023 Household Income $150,000-$199,999 (Esri)2023 Household Income $200,000 or greater (Esri)2023 Median Household Income (Esri)2023 Average Household Income (Esri)2023 Per Capita Income (Esri)2023 Households by Income Base (Esri)2023 Gini Index (Esri)2023 P90-P10 Ratio of Income Inequality (Esri)2023 P90-P50 Ratio of Income Inequality (Esri)2023 P50-P10 Ratio of Income Inequality (Esri)2023 80-20 Share Ratio of Income Inequality (Esri)2023 90-40 Share Ratio of Income Inequality (Esri)2023 Households in Low Income Tier (Esri)2023 Households in Middle Income Tier (Esri)2023 Households in Upper Income Tier (Esri)2023 Disposable Income less than $15,000 (Esri)2023 Disposable Income $15,000-$24,999 (Esri)2023 Disposable Income $25,000-$34,999 (Esri)2023 Disposable Income $35,000-$49,999 (Esri)2023 Disposable Income $50,000-$74,999 (Esri)2023 Disposable Income $75,000-$99,999 (Esri)2023 Disposable Income $100,000-$149,999 (Esri)2023 Disposable Income $150,000-$199,999 (Esri)2023 Disposable Income $200,000 or greater (Esri)2023 Median Disposable Income (Esri)2023 Home Value less than $50,000 (Esri)2023 Home Value $50,000-$99,999 (Esri)2023 Home Value $100,000-$149,999 (Esri)2023 Home Value $150,000-$199,999 (Esri)2023 Home Value $200,000-$249,999 (Esri)2023 Home Value $250,000-$299,999 (Esri)2023 Home Value $300,000-$399,999 (Esri)2023 Home Value $400,000-$499,999 (Esri)2023 Home Value $500,000-$749,999 (Esri)2023 Home Value $750,000-$999,999 (Esri)2023 Home Value $1,000,000-$1,499,999 (Esri)2023 Home Value $1,500,000-$1,999,999 (Esri)2023 Home Value $2,000,000 or greater (Esri)2023 Median Home Value (Esri)2023 Average Home Value (Esri)2028 Total Population (Esri)2028 Household Population (Esri)2028 Population Density (Pop per Square Mile) (Esri)2028 Total Households (Esri)2028 Average Household Size (Esri)2023-2028 Population: Compound Annual Growth Rate (Esri)2023-2028 Households: Compound Annual Growth Rate (Esri)2023-2028 Per Capita Income: Compound Annual Growth Rate (Esri)2023-2028 Median Household Income: Compound Annual Growth Rate (Esri)2028 Diversity Index (Esri)2028 Median Household Income (Esri)2028 Average Household Income (Esri)2028 Per Capita Income (Esri)
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TwitterRace is a social and historical construct, and the racial categories counted by the census change over time so the process of constructing stable racial categories for these 50 years out of census data required complex and imperfect decisions. Here we have used historical research on early 20th century southern California to construct historic racial categories from the IPUMS full count data, which allows us to track groups that were not formally classified as racial groups in some census decades like Mexican, but which were important racial categories in southern California. Detailed explanation of how we constructed these categories and the rationale we used for the decisions we made can be found here. Layers are symbolized to show the percentage of each of the following groups from 1900-1940:AmericanIndian Not-Hispanic, AmericanIndian Hispanic, Black non-Hispanic, Black-Hispanic, Chinese, Korean, Filipino and Japanese, Mexican, Hispanic Not-Mexican, white non-Hispanic. The IPUMS Census data is messy and includes some errors and undercounts, making it hard to map some smaller populations, like Asian Indians (in census called Hindu in 1920) and creating a possible undercount of Native American populations. The race data mapped here also includes categories that may not have been socially meaningful at the time like Black-Hispanic, which generally would represent people from Mexico who the census enumerator classified as Black because of their dark skin, but who were likely simply part of Mexican communities at the time. We have included maps of the Hispanic not-Mexican category which shows very small numbers of non-Mexican Hispanic population, and American Indian Hispanic, which often captures people who would have been listed as Indian in the census, probably because of skin color, but had ancestry from Mexico (or another Hispanic country). This category may include some indigenous Californians who married into or assimilated into Mexican American communities in the early 20th century. If you are interested in mapping some of the other racial or ethnic groups in the early 20th century, you can explore and map the full range of variables we have created in the People's History of the IE IE_ED1900-1940 Race Hispanic Marriage and Age Feature layer.Suggested Citation: Tilton, Jennifer. People's History Race Ethnicity Dot Density Map 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. 2025Feature Layer CitationTilton, Jennifer, Tessa VanRy & Lisa Benvenuti. Race and Demographic Data 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. Additional contributing authors: Mackenzie Nelson, Will Blach & Andy Garcia Funding provided by: People’s History of the IE: Storyscapes of Race, Place, and Queer Space in Southern California with funding from NEH-SSRC Grant 2022-2023 & California State Parks grant to Relevancy & History. Source for Census Data 1900- 1940 Ruggles, Steven, Catherine A. Fitch, Ronald Goeken, J. David Hacker, Matt A. Nelson, Evan Roberts, Megan Schouweiler, and Matthew Sobek. IPUMS Ancestry Full Count Data: Version 3.0 [dataset]. Minneapolis, MN: IPUMS, 2021. Primary Sources for Enumeration District Linework 1900-1940 Steve Morse provided the full list of transcribed EDs for all 5 decades "United States Enumeration District Maps for the Twelfth through the Sixteenth US Censuses, 1900-1940." Images. FamilySearch. https://FamilySearch.org: 9 February 2023. Citing NARA microfilm publication A3378. Washington, D.C.: National Archives and Records Administration, 2003. BLM PLSS Map Additional Historical Sources consulted include: San Bernardino City Annexation GIS Map Redlands City Charter Proposed with Ward boundaries (Not passed) 1902. Courtesy of Redlands City Clerk. Redlands Election Code Precincts 1908, City Ordinances of the City of Redlands, p. 19-22. Courtesy of Redlands City Clerk Riverside City Charter 1907 (for 1910 linework) courtesy of Riverside City Clerk. 1900-1940 Raw Census files for specific EDs, to confirm boundaries when needed, accessed through Family Search. If you have additional questions or comments, please contact jennifer_tilton@redlands.edu.