This map shows the percentage of White population in the U.S. (Non-Hispanic or Latino). The pattern is shown by states, counties, and Census tracts. Zoom or search for anywhere in the U.S. 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 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. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map are updated annually when the newest estimates are released by ACS and updated in ArcGIS Living Atlas. For more detailed metadata, click on one of the layers listed below. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

In 2024, white Americans remained the largest racial group in the United States, numbering just over 254 million. Black Americans followed at nearly 47 million, with Asians totaling around 23 million. Hispanic residents, of any race, constituted the nation’s largest ethnic minority. Despite falling fertility, the U.S. population continues to edge upward and is expected to reach 342 million in 2025. International migrations driving population growth The United States’s population growth now hinges on immigration. Fertility rates have long been in decline, falling well below the replacement rate of 2.1. On the other hand, international migration stepped in to add some 2.8 million new arrivals to the national total that year. Changing demographics and migration patterns Looking ahead, the U.S. population is projected to grow increasingly diverse. By 2060, the Hispanic population is expected to grow to 27 percent of the total population. Likewise, African Americans will remain the largest racial minority at just under 15 percent.

This statistic shows the population of the United States in the final census year before the American Civil War, shown by race and gender. From the data we can see that there were almost 27 million white people, 4.5 million black people, and eighty thousand classed as 'other'. The proportions of men to women were different for each category, with roughly 700 thousand more white men than women, over 100 thousand more black women than men, and almost three times as many men than women in the 'other' category. The reason for the higher male numbers in the white and other categories is because men migrated to the US at a higher rate than women, while there is no concrete explanation for the statistic regarding black people.

About this dataset

Context

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

Key observations

The percent distribution of Country Club Hills population by race (across all racial categories recognized by the U.S. Census Bureau): 8% are white, 87.79% are Black or African American, 0.46% are Asian, 1.47% are some other race and 2.27% 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 Country Club Hills
• Population: The population of the racial category (excluding ethnicity) in the Country Club Hills is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Country Club Hills 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 Country Club Hills Population by Race & Ethnicity. You can refer the same here

This map shows the percentage of people who identify as something other than non-Hispanic white throughout the U.S. 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. The data is from the U.S. Census Bureau's American Community Survey (ACS). The figures in this map are updated annually when the newest estimates are released by ACS and updated in ArcGIS Living Atlas. For more detailed metadata, click on one of the layers listed below. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

A line chart that shows % of total population that is White, not Hispanic, by region

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Country Life Acres by race. It includes the distribution of the Non-Hispanic population of Country Life Acres across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Country Life Acres across relevant racial categories.

Key observations

Of the Non-Hispanic population in Country Life Acres, the largest racial group is White alone with a population of 74 (96.10% of the total Non-Hispanic population).

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 (for Non-Hispanic) for the Country Life Acres
• Population: The population of the racial category (for Non-Hispanic) in the Country Life Acres is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Country Life Acres total Non-Hispanic 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 Country Life Acres Population by Race & Ethnicity. You can refer the same here

Know Your Customer Dataset, Face Detection and Re-identification

  The dataset is created on the basis of Selfies and ID Dataset

80,000+ photos including 10,600+ document photos from 5,300 people from 28 countries. The dataset includes 2 photos of a person from his documents and 13 selfies. All people presented in the dataset are caucasian. The dataset contains a variety of images capturing individuals from diverse backgrounds and age groups. Photo documents contains only… See the full description on the dataset page: https://huggingface.co/datasets/UniqueData/caucasian-people-kyc-photo-dataset.

Among the 81 largest metropolitan areas (by population) in the United States, Knoxville, Tennessee was ranked first with **** percent of residents reporting as white, non-Hispanic in 2023.

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Town And Country by race. It includes the distribution of the Non-Hispanic population of Town And Country across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Town And Country across relevant racial categories.

Key observations

Of the Non-Hispanic population in Town And Country, the largest racial group is White alone with a population of 9,318 (83.18% of the total Non-Hispanic population).

https://i.neilsberg.com/ch/town-and-country-mo-population-by-race-and-ethnicity.jpeg" alt="Town And Country Non-Hispanic population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 (for Non-Hispanic) for the Town And Country
• Population: The population of the racial category (for Non-Hispanic) in the Town And Country is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Town And Country total Non-Hispanic 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 Town And Country Population by Race & Ethnicity. You can refer the same here

According to the 2021 Census, 81.7% of the population of England and Wales was white, 9.3% Asian, 4.0% black, 2.9% mixed and 2.1% from other ethnic groups.

Against the background of the worldwide protests against police violence and racism after the violent killing of the African-American George Floyd in the USA, this survey examines how racism is perceived in Germany and what experiences people with a migration background have had with racism in Germany. For this purpose, both people with and without a migration background are interviewed. The study asks about the prevalence of racist prejudices in the everyday life of the interviewees, about experiences with racism in different areas of life, about the feeling of security, recognition and well-being in German society and about trust in politics, political institutions and the police. In addition, respondents are asked how they assess the current use of politics in combating racism and in which areas more should be done.
1. Social participation and recognition: life satisfaction; fair share in life; factors for success in society (open); assessment of personal acceptance as an equal citizen, of personal possibilities to influence German politics and justice in Germany; trust in institutions (judiciary, federal government, media, police, authorities); attachment to the community/city of residence, the region, the federal state, Germany, the country of origin and the country of origin of the parents; personal feeling of security in Germany.

1. Living together in Germany: frequency of contact with people from a different ethnic background; assessment of living together with people from different ethnic backgrounds; reasons for problems in living together with people from different ethnic backgrounds in Germany (open); treatment of people from a different ethnic background compared to people from a German background (worse, same treatment or better).

2. Problem perception of racism in Germany: agreement with various statements about racism (most people in Germany do not differentiate according to the colour of someone´s skin, there is now too much talk about racism in Germany, which makes the problem bigger than it actually is, the racism debate is characterised by hysteria and oversensitivity, meanwhile there is also racism against white Germans in Germany, I´m not sure if I don´t sometimes act racist by mistake, racism nowadays only occurs in isolated cases, an action or statement can also be racist if it wasn´t meant that way at all, people from different cultures enrich Germany); perception of racism in Germany as a problem; perception of the frequency of violence against people with a different ethnic background as a problem in Germany; assessment of racism in Germany in comparison to other European countries and in comparison to the USA; assessment of racism in Germany today in comparison to the 1990s; future expectations with regard to the increase or decrease of racist prejudices and racist behaviour.

3. Definition of racism: assessment of racist situations (e.g. asking a non-white person where he/she originally comes from, addressing a person with a different ethnic background in simple German, etc.); groups of people affected by racism (people with a different skin colour, people who do not speak German without an accent, women with headscarves, people who visibly wear religious symbols or who belong to a non-Christian religion, people whose name sounds non-German); racist behaviour according to groups of people (everyone/individuals, majority of the population, educational institutions, police, media, parties, people whose name sounds non-German). (people with a different skin colour, people who do not speak German without an accent, women with headscarves, people who visibly wear religious symbols or belong to a non-Christian religion, people whose name sounds non-German); racist behaviour by groups of people (each individual, majority of the population, educational institutions, police, media, political parties, right-wing extremist individuals or groups); frequency of racist behaviour by groups of people; perception of racism in different areas of life (at work, in shops or in the service sector, in the housing market, in public, in leisure time, in the health or care sector, by offices or authorities, on the internet or in social networks, at school or kindergarten, by the police); assessment of the appropriateness of racial profiling.

4. Experiences of discrimination: question about the original country of origin; suspected reasons for the question about origin (appearance, accent, name, headscarf, clothing, because of accompanying persons, because of statements in conversation); appearance as a reason (hair, beard, face, skin colour, eyes or eye colour, headscarf, other item of clothing, other (open); personal experience of racially motivated discrimination according to areas of life and in the personal environment or by unknown third parties.

5. Anti-racist measures: opinion on renaming street names that contain terms perceived as racist or are named after racist perpetrators of...

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

Know Your Customer Dataset, Face Detection and Re-identification

The dataset is created on the basis of Selfies and ID Dataset

80,000+ photos including 10,600+ document photos from 5,300 people from 28 countries. The dataset includes 2 photos of a person from his documents and 13 selfies. All people presented in the dataset are caucasian. The dataset contains a variety of images capturing individuals from diverse backgrounds and age groups.

Photo documents contains only a photo of a person. All personal information from the document is hidden

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F9ad166a8728e7299087a69793e420918%2FFrame%2015%20(1).png?generation=1712143714014867&alt=media" alt="">

Documents in the dataset

• Passports
• International passport
• Driver licenses
• Student cards
• Health certificate
• Pensioner's ID
• Pass to work
• Other documents

The dataset can be utilized for a wide range of tasks, including face recognition, emotion detection, age estimation, gender classification, or any problem related to human image analysis.

👉 Legally sourced datasets and carefully structured for AI training and model development. Explore samples from our dataset of 95,000+ human images & videos - Full dataset

Metadata for the full dataset:

• assignment_id - unique identifier of the media file
• worker_id - unique identifier of the person
• age - age of the person
• gender - gender of the person
• country - country of the person
• ethnicity - ethnicity of the person
• photo_1_extension, photo_2_extension, …, photo_15_extension - photo extensions in the dataset
• photo_1_resolution, photo_2_resolution, …, photo_15_resolution - photo resolution in the dataset

Statistics for the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F5a5be7a59953aa5e05014dbc88c7740b%2FFrame%2093.png?generation=1712832246364646&alt=media" alt="">

🧩 This is just an example of the data. Leave a request here to learn more

Content

The dataset consists of: - files - includes 7 folders corresponding to each person and including 15 images (2 id photos and 13 selfies), - .csv file - contains information about the images and people in the dataset

File with the extension .csv

• id: id of the person,
• age - age of the person,
• gender - gender of the person,
• country - country of the person,
• id_1, id_2: link to access id photos,
• selfie_1, selfie_2, ..., selfie_13: link to access each of the 13 selfies of the person

🚀 You can learn more about our high-quality unique datasets here

keywords: biometric system, biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, object detection dataset, deep learning datasets, computer vision datset, human images dataset, human faces dataset, machine learning, image-to-image, re-identification, id photos, selfies and paired id, photos, id verification models, passport, id card image, digital photo-identification, caucasian people, caucasian dataset

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Country Life Acres by race. It includes the distribution of the Non-Hispanic population of Country Life Acres across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Country Life Acres across relevant racial categories.

Key observations

Of the Non-Hispanic population in Country Life Acres, the largest racial group is White alone with a population of 88 (97.78% of the total Non-Hispanic population).

https://i.neilsberg.com/ch/country-life-acres-mo-population-by-race-and-ethnicity.jpeg" alt="Country Life Acres Non-Hispanic population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 (for Non-Hispanic) for the Country Life Acres
• Population: The population of the racial category (for Non-Hispanic) in the Country Life Acres is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Country Life Acres total Non-Hispanic 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 Country Life Acres Population by Race & Ethnicity. You can refer the same here

This Opinion Poll was carried out between 26 March and 29 April 1997 in the fifteen Member States at the request of the Employment, Industrial Relations and Social Affairs Directorate (DGV) of the European Commission within the framework of Eurobarometer 47.1. It involved 16,154 people. It was commissioned as part of the European Year Against Racism and coordinated by INRA (Europe). The last poll of this kind was taken in 1988. The data were analysed under the responsibility of Jeanne Ben Brika and Gérard Lemaine (Ecole des Hautes Etudes en Sciences Sociales, Paris).

The results by volumes are distributed as follows:

• Volume A: Countries
• Volume AA: Groups of countries
• Volume A' (AP): Trends
• Volume AA' (AAP): Trends of groups of countries
• Volume B: EU/socio-demographics
• Volume B' (BP) : Trends of EU/ socio-demographics
• Volume C: Country/socio-demographics ---- Researchers may also contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer

Cultures of Anti-Racism in Latin America (CARLA) was a three-year project (January 2020 to May 2023) funded by the Arts and Humanities Research Council (UK) to explore how artists in Argentina, Brazil and Colombia address racial diversity in their work and how they use their art to challenge racism. The project was based in the University of Manchester and research teams focused on each country brought together senior and junior, UK-based and Latin American researchers in the social sciences and arts to work with a range of artists and performers to explore diverse practices, including Indigenous visual and performance arts in Brazil (including Indigenous hip-hop), Afro-Colombian visual art, poetry and dance, and Mapuche and Afro-Argentine theatre companies as well as an Argentine art collective that uses performance and visual arts as pedagogical and decolonial tools. Project researchers worked closely with artists and performers and collaborated with them in various public-facing activities.

The collaborations led to the production of items for an online exhibition (https://www.digitalexhibitions.manchester.ac.uk/s/carla-en/page/home; https://figshare.com/s/acbe67be51ceca9b4b86).

The data uploaded here consists of transcripts of: 1. six anonymised online interviews with Colombian people interested in Afro-Colombian music and dance; they talk about their personal trajectories and their relationship with Blackness and Black music and dance. 2. transcripts of four anonymised focus groups held online with Colombian participants interested in Afro-Colombian music and dance; in two groups, they talk about their feelings and thoughts about Afro-Colombian contemporary dance and, in two other groups, about champeta (an Afro-Colombian popular music style). 3. an anonymised transcript of an interview with an Indigenous Brazilian youth leader and journalist (EE) from the Guajajara people in Maranhão, Brazil. 4. a transcript of a recording made by Indigenous Brazilian artist Jaider Esbell about his work, especially recorded for the CARLA project. 5. an anonymised transcript of interviews with key participants in the exhibition Véxoa: Nós Sabemos, shown at the Pinacoteca de São Paulo, October 2020 to March 2021. 6. five anonymised transcripts of interviews with: an Indigenous Argentinian hip-hop group; four members of an Argentinian anti-racist art collective.

The data files are zipped into folders by country. An Excel spreadsheet and a read-me file are included with details of each file.

In a global context of persistent racism and racial inequality, alongside the growing "post-racial" denial of their importance, this project explored the role of the arts in challenging racism. The project aimed to investigate the sociality, practices and discourses of contemporary cultural producers working in literature and visual and performing arts who focus on issues of racial difference, racism and anti-racism in three Latin American contexts: Brazil, Colombia and Argentina.

Why the arts? We work on the basis that the arts have always played a crucial role in anti-racist movements, serving as important tools with which to protest against and educate about racism. The arts have the ability to mobilise emotions through narrative and performance, and this makes them well suited to deal with racism's dependence on an emotive logic. By combining expertise from the arts and the social sciences in a cultural studies approach, we sought to locate artistic practices that address racial inequality and racism in their social and cultural context; we aimed to map how the producers, their practices and their products circulate in the social world and produce effects there that contribute to the struggle against racism. While rationally devised social policy addressing socio-economic conditions is vital to correcting racial inequalities, it can simply by-pass, be undermined by and even exacerbate the visceral emotions that racial difference produces in a racially hierarchical society. It is these emotions we sought to approach and address through the medium of art and performance.

Why Latin America? Because the region has a long history in which "post-raciality" - by which we mean the tendency to deny or minimise the significance of racism and racial inequality, invoking a colour-blind universalism - has co-existed with marked racial inequality and with often veiled but still powerful racist attitudes. This paradoxical co-existence is becoming characteristic of other areas of the world, in the wake of post-World War II trends that made "race" politically toxic and made the denial of racism commonplace, while racial inequalities remain and even grow. We contend that the way struggles against racism in Latin America address this long-standing co-existence can hold lessons for anti-racism more widely. For example, the post-racial claim that increased inter-racial mixture indicates decreasing racism is belied by the fact that Latin American countries have often been majority mestizo (mixed-race) societies for over two centuries, without this having solved the problem of racial inequality and racism.

A notable feature of the project is that it encompasses anti-Black and anti-Indigenous racism in a region where practices and attitudes prejudicial to Indigenous people are often not labelled as racism, but also at a time at which this label is becoming increasingly popular in struggles against such prejudice, highlighting the structural dimensions of Indigenous disadvantage. A further strength of the project is its comparative approach, which seeks to use the rather different racial formations of Argentina, Brazil and Colombia to assess how generic or country-specific anti-racism strategies are.

Research teams in each country brought together senior and junior, UK-based and Latin American researchers in the social sciences and arts to work with a range of artists and performers to explore diverse practices, including for example Indigenous literatures, visual arts and cinema in Brazil, hip-hop music in Brazil and Colombia, Afro-Colombian art and an Indigenous-Black organisation that uses performance as a pedagogical tool, and street dance and commercial music forms alongside literature and political art in Argentina. Project researchers worked closely with artists and performers and collaborated with them in project workshops, some of which also had a public-facing component.

This round of Eurobarometer surveys queried respondents on standard Eurobarometer measures, such as how satisfied they were with their present life, whether they attempted to persuade others close to them to share their views on subjects they held strong opinions about, whether they discussed political matters, and how they viewed the need for societal change. Additional questions focused on the respondents' knowledge of and opinions on the European Union (EU), including how well-informed they felt about the EU, what sources of information about the EU they used, whether their country had benefited from being an EU member, and the extent of their personal interest in EU matters. Respondents were asked how their present situation compared with five years ago, whether they thought it would improve over the next five years, and if in the last five years they themselves, a family member, or a close friend had been unemployed or if the company they worked for had "made people redundant," i.e., laid people off. Respondents were also asked about how much news they currently watched on TV, read about in newspapers, or listened to on the radio, how fair they felt the media coverage of the EU was, whether their image of the EU was positive or negative, and which groups or types of people (e.g., children, the elderly, politicians, teachers, lawyers, factory workers, farmers, etc.) had more and which had less advantages from their country's EU membership. Other questions focused on how satisfied respondents were with the way democracy worked in their country and in the EU, how important various European institutions were in the life of the EU and whether they trusted them, the amount of pride they had in their nationality, and if they were for or against EU features such as a single currency, an independent European Central Bank, a common foreign policy, a common defense and security policy, and a European Union that is responsible beyond national, regional, and local governments. Opinions were sought on possible EU social and political actions, which nonmember countries should become members, the role of the European Parliament, and whether the EU should have a constitution. Other topics of focus in the surveys included racism, general services, food labeling, and information and communication technologies. Several questions about people of different nationalities, religions, or cultures queried respondents as to whether they found these people disturbing, whether they themselves felt they were part of the majority or minority in their country, and if they had a parent or grandparent of a different nationality, race, religion, or culture. Respondents were asked to agree or disagree with a number of statements about issues involving minority groups and education, housing, social benefits, international sport, cultural life, religious practices, employment, and the economy. Additionally, respondent opinion was sought on the size of minority populations in their country, how relations with minorities could be improved, whether restrictions should be placed on minority workers from outside the EU, and the proper place in society for these minorities. A few questions also queried respondents about cultural and religious differences that immigrants (i.e., people who were not citizens of a member state of the EU) brought to the EU and how the EU should handle various situations involving this group of people. Questions regarding services of general interest, specifically mobile and fixed telephone services, electric, gas, and water supply services, postal services, transport services within towns/cities, and rail services between towns/cities, probed for respondent opinion on ease of access, price and contract fairness, quality of service, and clearness of service-provided information. For each service, respondents were asked whether in the last 12 months they had personally made a complaint about the service to any complaint-handling body and how they felt the situation was handled. Another section of the surveys queried respondents on how often they read food labels, if they thought there was too much or too little information on food labels, if they trusted and understood food labels, whether potential harm or benefit information should appear on the labels, who should be responsible for the information, and if food labels affected t

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Hill Country Village by race. It includes the distribution of the Non-Hispanic population of Hill Country Village across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Hill Country Village across relevant racial categories.

Key observations

Of the Non-Hispanic population in Hill Country Village, the largest racial group is White alone with a population of 565 (76.87% of the total Non-Hispanic population).

https://i.neilsberg.com/ch/hill-country-village-tx-population-by-race-and-ethnicity.jpeg" alt="Hill Country Village Non-Hispanic population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 (for Non-Hispanic) for the Hill Country Village
• Population: The population of the racial category (for Non-Hispanic) in the Hill Country Village is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Hill Country Village total Non-Hispanic 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 Hill Country Village Population by Race & Ethnicity. You can refer the same here

The survey, commissioned by the newsmagazine Suomen Kuvalehti, charted attitudes in Finland towards immigrants from different countries as well as beliefs about race. First, the respondents were asked to state their position on a scale from 0 to 10, where 10 indicated they hoped that Finland would be populated as much as possible by people of Finnish origin sharing the national values, and 0 that they hoped Finland would be populated as much as possible by people from a diversity of countries and ethnic backgrounds. Next, opinions were studied regarding how desirable or undesirable the respondents thought it was that immigrants of certain nationalities would come to Finland. The nationalities mentioned were Swedes, Germans, Russians, Estonians, US Americans, Somalis, Kosovars, Iraqis, Afghans, Syrians, Chinese, Thai and Ukrainians. The respondents were also asked to what extent they agreed with the following four statements: 'The mental abilities of black Africans are lower than those of white people living in Western countries', ' All people have equal value regardless of the colour of their skin or ethnic background', 'The white European race should be prevented from being mixed with darker races because otherwise the original population of Europe will become extinct before long ', and 'There is no such thing as 'race' since all human beings are genetically very much alike'. One question studied whether the respondents thought the Finnish media reported more negatively or positively on the Perussuomalaiset party (the Finns Party) than on the other political parties. Background variables included the respondent's gender, age, region of residence (NUTS3), major region of residence (NUTS2), city or type of municipality, education, occupational status and economic activity, household composition, number and ages of children living at home, total gross annual income of the household, and type of housing.