In Soviet Russia (RSFSR) in 1939 and 1959, ethnic Russians made up the largest share of the total population, with a share of approximately 83 percent. Tatars were the second largest ethnic group, followed by Ukrainians. Russians were consistently the largest ethnic group in the Soviet Union as a whole, with an overall share of 53 percent in 1979.
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ethnic groups in Russia. name, image, country of origin, continent of origin, Language, Religion, religion, population
Only four percent of Russians were open to seeing people of Central Asian ethnicities among their family members as of December 2021. Even though countries like Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan used to be part of the Soviet Union, 26 percent of respondents were against letting people from ethnic groups originating in Central Asia to reside in Russia.
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Context
The dataset tabulates the population of Russia by race. It includes the population of Russia across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Russia across relevant racial categories.
Key observations
The percent distribution of Russia population by race (across all racial categories recognized by the U.S. Census Bureau): 99.05% are white and 0.95% are multiracial.
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Russia Population by Race & Ethnicity. You can refer the same here
Throughout the history of the Soviet Union, Russians were consistently the largest ethnic group in the USSR. Of a total population of 262 million people in 1979, the share who were Russian was over 137 million, which is equal to roughly 52 percent. In 1989, the total population of the Soviet Union was almost 286 million, with the ethnic Russian population at 145 million, or 51 percent. Following the dissolution of the Soviet Union in 1991, the Tatars were the only of the ten largest ethnic groups not to be given their own independent country, with Tatarstan instead becoming one of Russia's federal republics.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset tabulates the population of Russia town by race. It includes the population of Russia town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Russia town across relevant racial categories.
Key observations
The percent distribution of Russia town population by race (across all racial categories recognized by the U.S. Census Bureau): 92.97% are white, 0.91% are Black or African American, 0.71% are American Indian and Alaska Native, 0.36% are Asian and 5.04% are multiracial.
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Russia town Population by Race & Ethnicity. You can refer the same here
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.
Approximately 98 percent of female criminals in Russia in 2021 possessed a Russian passport. Among men who committed a crime in the country, nearly four percent had a nationality of another state or were classified as stateless persons.
Languages:Percent Russian Speakers: Basic demographics by census tracts in King County based on current American Community Survey 5 Year Average (ACS). Included demographics are: total population; foreign born; median household income; English language proficiency; languages spoken; race and ethnicity; sex; and age. Numbers and derived percentages are estimates based on the current year's ACS. GEO_ID_TRT is the key field and may be used to join to other demographic Census data tables.
People of African descent were the ethnic group with the furthest social distance to Russians as of December 2021, followed by Central Asia ethnicities. The highest social acceptance was recorded for Jews and Ukrainians.
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Context
The dataset tabulates the Non-Hispanic population of Russia by race. It includes the distribution of the Non-Hispanic population of Russia across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Russia across relevant racial categories.
Key observations
With a zero Hispanic population, Russia is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 726 (99.05% of the total Non-Hispanic population).
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Russia Population by Race & Ethnicity. You can refer the same here
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Cystic fibrosis (CF) is a common monogenic disease caused by pathogenic variants in the CFTR gene. The distribution and frequency of CFTR variants vary in different countries and ethnic groups. The spectrum of pathogenic variants of the CFTR gene was previously studied in more than 1,500 CF patients from different regions of the European and North Caucasian region of Russia and the spectrum of the most frequent pathogenic variants of the CFTR gene and ethnic features of their distribution were determined. To assess the population frequency of CFTR gene mutations some of the common variants were analyzed in the samples of healthy unrelated individuals from the populations of the European part of the Russian Federation: 1,324 Russians from four European regions (Pskov, Tver, Rostov, and Kirov regions), representatives of five indigenous ethnic groups of the Volga-Ural region [Mari (n = 505), Udmurts (n = 613), Chuvash (n = 780), Tatars (n = 704), Bashkirs (n = 517)], and six ethnic groups of the North Caucasus [Karachay (n = 324), Nogais (n = 118), Circassians (n = 102), Abazins (n = 128), Ossetians (n = 310), and Chechens (n = 100)]. The frequency of common CFTR mutations was established in studied ethnic groups. The frequency of F508del mutation in Russians was found to be 0.0056 on average, varying between four regions, from 0.0027 in the Pskov region to 0.0069 in the Rostov region. Three variants W1282X, 1677delTA, and F508del were identified in the samples from the North Caucasian populations: in Karachay, the frequency of W1282X mutation was 0.0092, 1677delTA mutation – 0.0032; W1282X mutation in the Nogais sample – 0.0127, the frequency of F508del mutations was 0.0098 and 1677delTA – 0.0098 in Circassians; in Abazins F508del (0.0039), W1282X (0.0039) and 1677delTA (0.0117) mutations were found. In the indigenous peoples of the Volga-Ural region, the maximum frequency of the F508del mutation was detected in the Tatar population (0.099), while this mutation was never detected in the Mari and Bashkir populations. The E92K variant was found in Chuvash and Tatar populations. Thus, interethnic differences in the spectra of CFTR gene variants were shown both in CF patients and in healthy population of the European and North Caucasian part of Russia.
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We examine ethnic divisions in conflict-affected and post-conflict societies. Conventional wisdom tells us that societies that have experienced violent struggles in which individuals of different ethnic groups have (been) mobilized against each other are likely to become ossified along ethnic lines. Indeed, both policy-makers and scholars often assume that such divisions are one of the main challenges that must be overcome to restore peace after war. We comparatively assess this hypothesis by mapping dimensions of social distance among 4,000 survey respondents in Bosnia and the North Caucasus region of Russia. The surveys were carried out in December 2005. Using multidimensional scaling, we do not find evidence for clear attitudinal cleavages among members of different ethnic groups in Bosnia. Nor do we find strong evidence for ethnic divisions in the North Caucasus, although our measurements of social distance reveal a difference between Russians and ethnic minority groups.
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Russian Federation - Net Issues of International Debt Securities for All Issuers, All Maturities, Nationality of Issuer in Russia was -3038.00000 Mil. of US $ in January of 2025, according to the United States Federal Reserve. Historically, Russian Federation - Net Issues of International Debt Securities for All Issuers, All Maturities, Nationality of Issuer in Russia reached a record high of 30072.00000 in July of 2012 and a record low of -11229.00000 in January of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for Russian Federation - Net Issues of International Debt Securities for All Issuers, All Maturities, Nationality of Issuer in Russia - last updated from the United States Federal Reserve on July of 2025.
Nearly 1.8 thousand people whose former citizenship was Russian acquired the French nationality in 2020. Furthermore, over 1.5 thousand individuals and over 800 received the Finnish and the Belgian citizenship, respectively.
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Thailand Tourism Receipts by Nationality: Russia data was reported at 4,057.760 THB mn in Jun 2018. This records a decrease from the previous number of 5,193.260 THB mn for May 2018. Thailand Tourism Receipts by Nationality: Russia data is updated monthly, averaging 8,034.660 THB mn from Jan 2016 (Median) to Jun 2018, with 30 observations. The data reached an all-time high of 17,918.480 THB mn in Jan 2018 and a record low of 3,471.730 THB mn in Jul 2016. Thailand Tourism Receipts by Nationality: Russia data remains active status in CEIC and is reported by Ministry of Tourism and Sport. The data is categorized under Global Database’s Thailand – Table TH.Q010: Tourism Receipts by Nationality.
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Russian Federation - Amounts Outstanding of International Debt Securities for All Issuers, All Maturities, Nationality of Issuer in Russia was 115597.00000 Mil. of US $ in January of 2025, according to the United States Federal Reserve. Historically, Russian Federation - Amounts Outstanding of International Debt Securities for All Issuers, All Maturities, Nationality of Issuer in Russia reached a record high of 274477.00000 in October of 2013 and a record low of 50.00000 in October of 1984. Trading Economics provides the current actual value, an historical data chart and related indicators for Russian Federation - Amounts Outstanding of International Debt Securities for All Issuers, All Maturities, Nationality of Issuer in Russia - last updated from the United States Federal Reserve on July of 2025.
Abstract copyright UK Data Service and data collection copyright owner.The New Baltic Barometer (NBB) was launched in 1993 to reflect opinions in three multi-ethnic societies, Estonia, Latvia and Lithuania, incorporated into the Soviet Union as a consequence of the Second World War. There were six NBB surveys conducted from 1993 to 2004, with many questions repeated to show trends. From 2001, the NBB was merged with the New Democracies Barometer to form New Europe Barometer (available from the UK Data Archive under GN 33355). Therefore the last two NBB surveys are available under SN 5242 and SN 5243 which are part of the New Europe Barometer series. Whereas political rhetoric often describes all people of a given nationality as thinking alike, election results show differences of opinion. The NBB documents differences within every nationality in the region along lines of age, education, economic circumstances and gender. Differences within each nationality may be paralleled by similarities between nationalities. Comparisons with the Russians in Russia can be made through the New Russia Barometer (available at the Archive under GN 33374) survey. Further information about the NBB survey series is available on the Baltic Voices web site. Additional information about all the Barometer survey series managed by the CSPP can be found on the CSPP Barometer Surveys web site. New Baltic Barometer III, 1996 is the third study in the series.
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Russian Federation - Amount Outstanding Due within One Year of International Debt Securities for All Issuers, Nationality of Issuer in Russia was 11387.00000 Mil. of US $ in January of 2025, according to the United States Federal Reserve. Historically, Russian Federation - Amount Outstanding Due within One Year of International Debt Securities for All Issuers, Nationality of Issuer in Russia reached a record high of 45322.00000 in July of 2017 and a record low of 0.00000 in October of 1984. Trading Economics provides the current actual value, an historical data chart and related indicators for Russian Federation - Amount Outstanding Due within One Year of International Debt Securities for All Issuers, Nationality of Issuer in Russia - last updated from the United States Federal Reserve on July of 2025.
In Soviet Russia (RSFSR) in 1939 and 1959, ethnic Russians made up the largest share of the total population, with a share of approximately 83 percent. Tatars were the second largest ethnic group, followed by Ukrainians. Russians were consistently the largest ethnic group in the Soviet Union as a whole, with an overall share of 53 percent in 1979.