This ethnicity dataset (GREG) is a digital version of the paper Soviet Narodov Mira atlas created in 1964. In 2010 the GREG (Geo-referencing of ethnic groups) project, used maps and data drawn from the Narodov Mira atlas to create a GIS (Geographic Information Systems) version of the atlas (2010). ETH ZurichFirst developed by G.P. Murdock in the 1940s, is an ethnographic classification system on human behavior, social life and customs, material culture, and human-ecological environments (2003). University of California

This map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?

45816 Global import shipment records of Ethnic with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

ESRI DATA: World Countries and World Administrative Areas; 2010 US Census datasets with their new geometry and attributes. Block Group, Tract, County and State are all represented as polygons with over 40 attribute fields containing population totals by age and race, along with family and household information. Census Blocks are represented as points with total population and household information; European demographics datasets, North America Street Map, World Base Maps, mainly topographic data such as roads, lakes, administrative boundaries

The stereotype content model (SCM), originating in the United States and generalized across nearly 50 countries, has yet to address ethnic relations in one of the world’s most influential nations. Russia and the United States are somewhat alike (large, powerful, immigrant-receiving), but differ in other ways relevant to intergroup images (culture, religions, ideology, and history). Russian ethnic stereotypes are understudied, but significant for theoretical breadth and practical politics. This research tested the SCM on ethnic stereotypes in a Russian sample (N = 1115). Study 1 (N = 438) produced an SCM map of the sixty most numerous domestic ethnic groups (both ethnic minorities and immigrants). Four clusters occupied the SCM warmth-by-competence space. Study 2 (N = 677) compared approaches to ethnic stereotypes in terms of status and competition, cultural distance, perceived region, and four intergroup threats. Using the same Study 1 groups, the Russian SCM map showed correlated warmth and competence, with few ambivalent stereotypes. As the SCM predicts, status predicted competence, and competition negatively predicted warmth. Beyond the SCM, status and property threat both were robust antecedents for both competence and warmth for all groups. Besides competition, cultural distance also negatively predicted warmth for all groups. The role of the other antecedents, as expected, varied from group to group. To examine relative impact, a network analysis demonstrated that status, competition, and property threat centrally influence many other variables in the networks. The SCM, along with antecedents from other models, describes Russian ethnic-group images. This research contributes: (1) a comparison of established approaches to ethnic stereotypes (from acculturation and intergroup relations) showing the stability of the main SCM predictions; (2) network structures of the multivariate dependencies of the considered variables; (3) systematically cataloged images of ethnic groups in Russia for further comparisons, illuminating the Russian historical, societal, and interethnic context.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

This statistic shows the share of ethnic groups in Australia in the total population. 33 percent of the total population of Australia are english.

Australia’s population

Australia’s ethnic diversity can be attributed to their history and location. The country’s colonization from Europeans is a significant reason for the majority of its population being Caucasian. Additionally, being that Australia is one of the most developed countries closest to Eastern Asia; its Asian population comes as no surprise.

Australia is one of the world’s most developed countries, often earning recognition as one of the world’s economical leaders. With a more recent economic boom, Australia has become an attractive country for students and workers alike, who seek an opportunity to improve their lifestyle. Over the past decade, Australia’s population has slowly increased and is expected to continue to do so over the next several years. A beautiful landscape, many work opportunities and a high quality of life helped play a role in the country’s development. In 2011, Australia was considered to have one of the highest life expectancies in the world, with the average Australian living to approximately 82 years of age.

From an employment standpoint, Australia has maintained a rather low employment rate compared to many other developed countries. After experiencing a significant jump in unemployment in 2009, primarily due to the world economic crisis, Australia has been able to remain stable and slightly increase employment year-over-year.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

This database, including both datasets and spatial shape files, contains information on occupation, school attendance, nativity, and race of the Boston population, by ward, for the years 1880, 1900, and 1930. This database can be used to visualize the profound changes in the economic, educational, and ethnic composition of Boston between 1880 and 1930. It illustrates, among other changes, the great expansion of secondary school enrollment, the decline of youth participation in the work force, the growth of white-collar jobs, the decline of unskilled labor, and the geographical distribution of the Boston Irish, Italian, Jewish, and African-American populations over time. This contextual knowledge is useful for historians researching this time period, and useful to non-historians by depicting the origins of fundamental changes whose legacy is still present in Boston today. The underlying data are drawn from the Integrated Public Use Microdata Series maintained by the University of Minnesota (see documentation for full citation). The data contained here can also be viewed through an interactive map hosted by BostonMap (http://worldmap.harvard.edu/maps/historical_boston).

GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.

With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.

Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.

Primary Use Cases for GapMaps Live includes:

1. Retail Site Selection - Identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers and where to find more of them.
3. Analyse your catchment areas at a granular grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
6. Customer Profiling
7. Target Marketing
8. Market Share Analysis

Some of features our clients love about GapMaps Live include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.

This map shows the percentage of people who identify as something other than non-Hispanic white throughout the US according to the most current American Community Survey. The pattern is shown by states, counties, and Census tracts. Zoom or search for anywhere in the US to see a local pattern. Click on an area to learn more. Filter to your area and save a new version of the map to use for your own mapping purposes.The Arcade expression used was: 100 - B03002_calc_pctNHWhiteE, which is simply 100 minus the percent of population who identifies as non-Hispanic white. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map update automatically annually when the newest estimates are released by ACS. For more detailed metadata, visit the ArcGIS Living Atlas Layer: ACS Race and Hispanic Origin Variables - Boundaries.The data on race were derived from answers to the question on race that was asked of individuals in the United States. The Census Bureau collects racial data in accordance with guidelines provided by the U.S. Office of Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. The categories represent a social-political construct designed for collecting data on the race and ethnicity of broad population groups in this country, and are not anthropologically or scientifically based. Learn more here.Other maps of interest:American Indian or Alaska Native Population in the US (Current ACS)Asian Population in the US (Current ACS)Black or African American Population in the US (Current ACS)Hawaiian or Other Pacific Islander Population in the US (Current ACS)Hispanic or Latino Population in the US (Current ACS) (some people prefer Latinx)Population who are Some Other Race in the US (Current ACS)Population who are Two or More Races in the US (Current ACS) (some people prefer mixed race or multiracial)White Population in the US (Current ACS)Race in the US by Dot DensityWhat is the most common race/ethnicity?

1023 Global import shipment records of Ethnic Bags with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

609 Global import shipment records of Ethnic Indian Wear with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

32 Active Global Ethnic Indian Wear buyers list and Global Ethnic Indian Wear importers directory compiled from actual Global import shipments of Ethnic Indian Wear.

This dot map shows three kinds of urban transitions. First, there are indeed areas where changes take place at very precise boundaries — such as between Lawndale and the Little Village, or Austin and Oak Park — and Chicago has more of these stark borders than most cities in the world. But transitions also take place through gradients and gaps as well, especially in the northwest and southeast. Using graphic conventions which allow these other possibilities to appear takes much more data, and requires more nuance in the way we talk about urban geography, but a cartography without boundaries can also make simplistic policy or urban design more difficult — in a good way.

This map compares homeownership rates between households with a non-Hispanic White householder and households with a Black or African American householder. This map shows us where there is a disparity in home ownership based on race/ethnicity. The pattern is shown at the state, county, and tract levels. Zoom or pan around the map to explore the map. You can also search for your city and explore the pattern in your local area. If you zoom out, you can see the nationwide pattern. The data comes from the most current release of American Community Survey (ACS) estimates from the U.S. Census Bureau. The layer being used in this map can be found here, and also within ArcGIS Living Atlas of the World. Click here to find more ACS layers within Living Atlas. Note: areas where there are no Black or White householders, no symbol is shown. This map compares areas where there are both White and Black householders.

Global and regional incidence, prevalence and YLDs of PCOS.

(UNCLASSIFIED) There are three main ethnolinguistic groups that made up ethnicity in Liberia; Mel, Mande, and Kru. The ethnic mix of Liberia has contributed to a rich culture as well as ethnic tension. It is common for politics in West Africa to divide along ethnic lines. Ethnic tension along with poor economic and social conditions and political instability were the leading causes for the two recent civil wars in the country. This first began in 1989 when the National Patriotic Front of Liberia, led by Charles Taylor, rose up against the Kran dominant government lead by Samuel Doe. The first civil war ended in 1997 with Charles Taylor formally voted into power. During the civil war Taylor commonly targeted Muslim Mande populations and the Kran for being the two groups most associated with the Doe regime. The opposition to Taylor retaliated by attacking Christian sites. Taylor’s regime was chaotic which led to a second civil war that began in 1999 with full scale war in 2003; a cease fire was signed the same year which ended the civil war. The actions during both civil wars show how politics and ethnicity go hand in hand and can produce ethnoreligious violence. Many in Liberia participate in secret societies known as hale, this is the most controlling and unifying force in Liberian culture with most participants belonging to one or more societies. They are both religious and political in nature and lay out acceptable and unacceptable behavior. There are numerous different hale societies offering regulations on how someone should act in society. The two most important hale societies are the men’s Poro and the female’s Sande, with participants joining at puberty to be taught the ideals of manhood and womanhood. Initiations are secret and performed in the forest. Reports state that initiation into the Sande society often includes female genital mutilation while boys undergo circumcisions in the Poro society. Belonging to either the Poro or Sande society is so important among traditional communities that those who do not join are not considered a member of the village, clan, or tribe. Mande - The Mande people group is the largest ethnicity in Liberia and has multiple subgroups. Agriculture, trade, and animal husbandry are common economic activities among the Mande people. They are patrilineal and the oldest male serves as the lineage head. Class structure is also common among Mande people typically consisting of royal, noble, commoner, artisan, and former slave classes. The largest Mande subgroup are the Kpelle and alone they account for 20.3 percent of the total Liberian population. The Kpelle organize themselves into many chiefdoms each of which are led by a paramount chief. While mass conversion to Christianity happened in the nineteenth century many still practice indigenous belief systems either alone or in combination with Christianity. Mel - The Mel group in Liberia is comprised of the Kissi and the Gola, 4.8 percent and 4.4 percent of the population respectively. Most Kissi are either Christian, animists, or a combination of the two. A small population, roughly 9 percent, is Muslim. Most are subsistence farmers or urban laborers. During the first civil war they were in conflict with the Kran. Kru – The Kru are organized based on patrilineal relationships and divided in many subgroups. As with many other ethnic groups in the region, while many have converted to Christianity there is still a significant portion that still adheres to indigenous beliefs or incorporates them into Christianity. Indigenous beliefs are passed through folklores and proverbs. Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name PEOPLEGP_1 - People Group level 1 PEOPLEGP_2 - People Group level 2 PEOPLEGP_3 - People Group level 3 PEOPLEGP_4 - People Group level 4 PEOPLEGP_5 - People Group level 5 ALT_NAMES - Alternative names or spellings for a people group COMMENTS - Comments or notes regarding the people group SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThe feature class was constructed by combining information from Murdock’s Map of Africa (1959) with other anthropological literature pertaining to Liberian ethnicity. The information was then processed through DigitalGlobe’s AnthropMapper program to generate more accurate ethnic coverage boundaries. Anthromapper uses geographical terrain features, combined with a watershed model, to predict the likely extent of ethnic and linguistic influence. The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Sources (HGIS)Anthromapper. DigitalGlobe, September 2014.Gonen, Amiram. The Encyclopedia of the Peoples of the World. New York: Henry Holt and Company, 1993.Levinson, David. Encyclopedia of World Cultures: Africa and the Middle East. Boston: G.K. Hall and Co., 1995.Minority Rights Group International. World Directory of Minorities and Indigenous Peoples, “Liberia Overview.” January 2005. Accessed September 23, 2014. http://www.minorityrights.org/directory.Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.Olson, James S. The Peoples of Africa: An Ethnohistorical Dictionary. Westport: Greenworod Press, 1996.The Diagram Group. Encyclopedia African Peoples. London: Diagram Visual Information, 2000.Yakan, Mohamad Z. Almanac of African Peoples and Nations. New Brunswick: Transaction Publishers, 1999.Sources (Metadata)Central Intelligence Agency. The World FactBook, “Liberia.” June 20, 2014. Accessed September 22, 2014. https://www.cia.gov/index.html.Gonen, Amiram. The Encyclopedia of the Peoples of the World. New York: Henry Holt and Company, 1993.Humanitarian News and Analysis, “Liberia: FGM continues in rural secrecy.” September 24, 2008. Accessed September 23, 2014. http://www.irinnews.org/.Levinson, David. Encyclopedia of World Cultures: Africa and the Middle East. Boston: G.K. Hall and Co., 1995.Olson, James S. The Peoples of Africa: An Ethnohistorical Dictionary. Westport: Greenworod Press, 1996.The Diagram Group. Encyclopedia African Peoples. London: Diagram Visual Information, 2000.Vogel, Health. Blogging without Maps: a Journey through Liberia, “Societies within Society – The Secret Societies of Liberia.” June 16, 2012. Accessed September 23, 2014. http://bloggingwithoutmaps.blogspot.com/.Yakan, Mohamad Z. Almanac of African Peoples and Nations. New Brunswick: Transaction Publishers, 1999.

Do Black households make as much as the typical household in the US? This map shows that this doesn't seem to be the case. This map compares the median household income of households with Black householders compared to the 2020 US median household income: $67,340. If the Black households in a county make as much as a "typical" household, the county is shown in turquoise. If Black households in a county make less than the US median income, it is shown in orange. The size of the symbol highlights where there are the highest counts of Black population in the US.The data comes from County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. The layer used in the map comes from ArcGIS Living Atlas of the World, and the full documentation for the layer can be found here.

Do Black households make as much as the "typical" household in their county? This map shows that this doesn't seem to be the case. This map compares the median household income of households with Black householders compared to the median household income of that county. If the Black households in a county make as much as a "typical" household in their county, the county is shown in turquoise. If Black households in a county make less than the median income of their county, it is shown in orange. The size of the symbol highlights where there are the highest counts of black population in the US.The data comes from County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. The layer used in the map comes from ArcGIS Living Atlas of the World, and the full documentation for the layer can be found here.