Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of New Britain by race. It includes the population of New Britain across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Britain across relevant racial categories.
Key observations
The percent distribution of New Britain population by race (across all racial categories recognized by the U.S. Census Bureau): 82.88% are white, 4.57% are Black or African American, 0.35% are American Indian and Alaska Native, 5.78% are Asian, 0.39% are some other race and 6.02% 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 New Britain Population by Race & Ethnicity. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset represents ethnic group (19 tick-box level) by economic activity status and by occupation, for England and Wales combined. The census data are also broken down by age and by sex for each subtopic.
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
This dataset shows population counts for usual residents aged between 16 to 64 years old only. This is to focus on ethnic groups differences among the working age. Population counts in these tables may be different from other publications which use different age breakdowns.
"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.
This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.
For quality information in general, please read more from here.
For specific quality information about labour market, please read more from here
Ocupation counts classifiy people who were in employment between 15 March and 21 March 2021, by the SOC code that represents their current occupation. (Occupation is classified using the Standard Occupation Classification 2020 version). Details of SOC code can be found here.
Ethnic Group (19 tick-box level)
These are the 19 ethnic group used in this dataset:
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset represents ethnic group (19 tick-box level) by highest level qualification, for England and Wales combined. The data are also broken down by age and by sex.
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.
This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021. This dataset shows population counts for usual residents aged 16+ Some people aged 16 years old will not have completed key stage 4 yet on census day, and so did not have the opportunity to record any qualifications on the census.
These estimates are not comparable to Department of Education figures on highest level of attainment because they include qualifications obtained outside England and Wales.
For quality information in general, please read more from here.
Ethnic Group (19 tick-box level)
These are the 19 ethnic group used in this dataset:
No qualifications
No qualifications
Level 1
Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills
Level 2
5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma
Apprenticeship
Apprenticeship
Level 3
2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma
Level 4 +
Degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)
Other
Vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of England by race. It includes the population of England across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of England across relevant racial categories.
Key observations
The percent distribution of England population by race (across all racial categories recognized by the U.S. Census Bureau): 67.17% are white, 24.82% are Black or African American, 0.31% are American Indian and Alaska Native, 4.02% are some other race and 3.67% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 England Population by Race & Ethnicity. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Ethnicity pay gap estimates for 2018 across different ethnicity breakdowns using the Annual Population Survey.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Dataset population: Persons
Country of birth
Country of birth is the country in which a person was born. This topic records whether the person was born in or if they were not born in a country.
For the full country of birth classification in England and Wales, please see the National Statistics Country Classification.
Ethnic group
Ethnic group classifies people according to their own perceived ethnic group and cultural background.
This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the 'Irish' response category. This topic was created as part of the commissioned table processing.
This project is the first census of all local councillors in all four constitutive nations of the UK, conducted in 2018 and 2019. The local level, so important to our democracy, is too often ignored, and political representation is predominantly studied at the national level. The particular importance of local level to ethnic representation cannot be overstated as it is often the first step in politics and political careers for many minority politicians, and a first line of contact for minority individuals and communities in need of help. This project seeks to fill this research gap and to put local representation at the heart of studying how ethnic minorities are politically represented in Britain. Our research design was developed to study the experiences of ethnic minority local councillors from visibly racialised backgrounds of both genders, to further our understandings of the mechanisms that underpin representational inequalities. We collected the ethnicity, gender and political party of every local councillor in the UK by referring to council websites. We sought to sample our interviewees to reflect a range of non-white backgrounds and political experience as well as gender balance. Interviewees were asked about how they became involved in local politics, their views on the extent of demand for greater diversity in local government and their experiences of running for selection and election for local government as well as serving as a local councillor. The collection consists of interview transcripts with 95 ethnic minority local councillors, candidates and activists, or white British councillors in local government leadership positions.Understandings of ethnic inequalities in the UK have developed substantially as a result of the work of The Centre on Dynamics of Ethnicity (CoDE). CoDE has successfully carried out an innovative programme of research, pursued challenging scientific objectives, and worked closely with a range of non-academic partners to impact on policy debates and development. In a rapidly evolving political and policy context, we propose a further, ambitious programme of work that takes us in new directions with a distinct focus. We will move beyond nuanced description to understanding processes and causes of ethnic inequalities, and build directly on our established experience in interdisciplinary and mixed methods working. In addition, we will use a co-production approach, working with a range of partners, including key public institutions such as the BBC, universities, political parties, ethnic minority NGOs, activists, and individuals, in order to frame and carry out our research in ways that will maximise our societal impact and lead to meaningful change. Our overarching objectives are to: -Understand how ethnic inequalities develop in a range of interconnected domains -Examine how these processes relate to and are shaped by other social categories, such as gender, class, religion and generation -Understand how ethnic inequalities take shape, and are embedded, in institutional spaces and practices -Work closely with policy and practice partners to meaningfully address enduring ethnic inequalities -Pursue methodological developments with interdisciplinary mixed methods and co-production at their core -Achieve ongoing high quality international academic impact Through a research plan divided into four work packages, we will examine ethnic inequalities in (1) higher education, (2) cultural production and consumption, (3) politics, representation and political parties and (4) pursue policy and institutional impact with our work in these areas. Alongside this, we are also conducting a programme of work on severe mental illness. These work packages will be organised around our ambition to understand, explain and impact on ethnic inequalities through a focus on institutional production of and responses to ethnic inequalities. At the core of our methodological approach is interdisciplinary and mixed methods working. Our quantitative work will be predominantly secondary data analysis, making the best use of the wide range of resources in the UK (e.g. Understanding Society, Destination of Leavers of Higher Education Survey, British Election Study, ONS Longitudinal Studies). Our qualitative work will be based around ethnographic approaches that are attentive to the ways in which social processes play out differently in different sites and institutions. We are informed especially by the approach of institutional ethnography which prioritises an attention to the lived, everyday experience of inequality, but aims to clarify the wider social relations in which such experiences are embedded and by which they are shaped. Thus institutional ethnographies will be developed which begin with exploring the experience of those directly involved in institutional settings as a route to understanding how structures and practices of institutions shape individuals' experiences and practices. Throughout our work we will integrate and mobilise research evidence to engage with a full range of partners in order to influence policy and practice development, public understanding and institutional practice. As well as having academic impact (journal articles, conferences, seminars, newsletters), our findings will be communicated directly to policy and advocacy organisations through a combination of well developed (blogs, Twitter, policy briefings) and emerging (podcasts and live streaming, museum and art exhibitions, online portal for individual narratives) forms of dissemination, and we will work directly with these organisations to achieve change. We hand coded all councillors’ ethnicity based on pictures included on the relevant council website, in cases where we lacked pictures or pictures were not definitive, we performed an online search of local media and councillors’ own professional websites. Finally, we used OriginsInfo software to auto-code the names of all councillors who we hand coded as ethnic minority, or unknown. OriginsInfo operates a proprietary algorithm to compare personal and family names with the ethnic, religious and cultural origin of 5,000,000 names from around the world. OriginsInfo matches forenames and surnames against a stored database of names and classifies them according to their most likely cultural origins by linguistic and religious affiliations. We used semi-structured interviews in order to gain insight into the ways in which ethnic minority councillors make sense of their social locations in their political environments, routes to office including selection and election processes, their experiences of serving on local councils and engaging with the constituents they represent. We sought to sample our interviewees to reflect a range of ethnic non-white backgrounds and political experience as well as gender balance. We conducted 94 semi-structured interviews, the majority of which were with British ethnic minority local councillors in England. Five of our female interviewees were of ethnic minority background who had been candidates for local council or parliament, rather than councillors. We also interviewed two local women activists of minority background working on political representation of women of colour.
The data collection contains population projections for UK ethnic groups and all local area by age (single year of age up to 100+) and sex. Included in the data set are also input data to the cohort component model that was used to project populations into the future-fertility rates, mortality rates, international migration flows and internal migration probabilities. Also included in data set are output data: Number of deaths, births and internal migrants. All data included are for the years 2011 to 2061. We have produced two ethnic population projections for UK local authorities, based on information on 2011 Census ethnic populations and 2010-2011-2012 ethnic components. Both projections align fertility and mortality assumptions to ONS assumptions. Where they differ is in the migration assumptions. In LEEDS L1 we employ internal migration rates for 2001 to 2011, including periods of boom and bust. We use a new assumption about international migration anticipating that the UK may leave the EU (BREXIT). In LEEDS L2 we use average internal migration rates for the 5 year period 2006-11 and the official international migration flow assumptions with a long term balance of +185 thousand per annum. This project aims to understand and to forecast the ethnic transition in the United Kingdom's population at national and sub-national levels. The ethnic transition is the change in population composition from one dominated by the White British to much greater diversity. In the decade 2001-2011 the UK population grew strongly as a result of high immigration, increased fertility and reduced mortality. Both the Office for National Statistics (ONS) and Leeds University estimated the growth or decline in the sixteen ethnic groups making up the UK's population in 2001. The 2011 Census results revealed that both teams had over-estimated the growth of the White British population and under-estimated the growth of the ethnic minority populations. The wide variation between our local authority projected populations in 2011 and the Census suggested inaccurate forecasting of internal migration. We propose to develop, working closely with ONS as our first external partner, fresh estimates of mid-year ethnic populations and their components of change using new data on the later years of the decade and new methods to ensure the estimates agree in 2011 with the Census. This will involve using population accounting theory and an adjustment technique known as iterative proportional fitting to generate a fully consistent set of ethnic population estimates between 2001 and 2011. We will study, at national and local scales, the development of demographic rates for ethnic group populations (fertility, mortality, internal migration and international migration). The ten year time series of component summary indicators and age-specific rates will provide a basis for modelling future assumptions for projections. We will, in our main projection, align the assumptions to the ONS 2012-based principal projection. The national assumptions will need conversion to ethnic groups and to local scale. The ten years of revised ethnic-specific component rates will enable us to study the relationships between national and local demographic trends. In addition, we will analyse a consistent time series of local authority internal migration. We cannot be sure, at this stage, how the national-local relationships for each ethnic group will be modelled but we will be able to test our models using the time series. Of course, all future projections of the population are uncertain. We will therefore work to measure the uncertainty of component rates. The error distributions can be used to construct probability distributions of future populations via stochastic projections so that we can define confidence intervals around our projections. Users of projections are always interested in the impact of the component assumptions on future populations. We will run a set of reference projections to estimate the magnitude and direction of impact of international migrations assumptions (net effect of immigration less emigration), of internal migration assumptions (the net effect of in-migration less out-migration), of fertility assumptions compared with replacement level, of mortality assumptions compared with no change and finally the effect of the initial age distribution (i.e. demographic potential). The outputs from the project will be a set of technical reports on each aspect of the research, journal papers submitted for peer review and a database of projection inputs and outputs available to users via the web. The demographic inputs will be subject to quality assurance by Edge Analytics, our second external partner. They will also help in disseminating these inputs to local government users who want to use them in their own ethnic projections. In sum, the project will show how a wide range of secondary data sources can be used in theoretically refined demographic models to provide us with a more reliable picture of how the UK population is going to change in ethnic composition. Base year data (2011) are derived from the 2011 census, vital statistics and ONS migration data. Subsequent population data are computed with a cohort component model.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset provides Census 2022 estimates for the Ethnic Group (in 21 categories) by age (in 20 categories) in Scotland.
A person's age on Census Day, 20 March 2022. Infants aged under 1 year are classified as 0 years of age.
Ethnic group classifies people according to their own perceived ethnic group and cultural background. Whilst the main ethnic group categories have not changed from the question asked in Census 2011, some of the detailed response options and write-in prompts for Scotland's Census 2022 were changed based on stakeholder engagement and subsequent question testing.
Details of classification can be found here
The quality assurance report can be found here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset represents ethnic group (19 tick-box level) by dwelling tenure and by occupancy rating, for England and Wales combined. The data are also broken down by age and by sex.
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.
This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.
All housing data in these tables do not include commual establishments.
For quality information in general, please read more from here.
For specific quality information about housing, please read more from here
Ethnic Group (19 tick-box level)
These are the 19 ethnic group used in this dataset:
Occupancy rating of bedrooms: 0 or more
A household’s accommodation has an ideal number of bedrooms or more bedrooms than required (under-occupied)
Occupancy rating of bedrooms: -1 or less
A household’s accommodation has fewer bedrooms than required (overcrowded)
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Dataset population: Dependent children
Ethnic group
Ethnic group classifies people according to their own perceived ethnic group and cultural background.
This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the Irish response category. This topic was created as part of the commissioned table processing.
Sex
The classification of a person as either male or female.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in England. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
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 England median household income by race. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Median pay and raw ethnicity pay gap estimates for 2012 to 2022 across different ethnicity breakdowns using the Annual Population Survey, UK.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset represents ethnic group (19 tick-box level) by general health, by disabled and non-disabled populations, and provision of unpaid care, for England and Wales combined. The data are also broken down by age and sex for each subtopic.
The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity, or physical appearance. Respondents could choose one out of 19 tick-box response categories, including write-in response options.
Total counts for some population groups may not match between published tables. This is to protect the confidentiality of individuals' data. Population counts have been rounded to the nearest 5 and any counts below 10 are suppressed, this is signified by a 'c' in the data tables.
"Asian Welsh" and "Black Welsh" ethnic groups were included on the census questionnaire in Wales only, these categories were new for 2021.
This dataset provides Census 2021 estimates that classify usual residents in England and Wales by ethnic group. The estimates are as at Census Day, 21 March 2021.
Read more about this quality notice.
The population base for unpaid care is usual residents aged 5 and above. 5-year age bands have been used for the majority of analysis; however, age groups "5 to 17" and "18 to 24" have been used to allow commentary on young carers and young working age carers.
Ethnic Group (19 tick-box level)
These are the 19 ethnic group used in this dataset:
_General health _
A person's assessment of the general state of their health from very good to very bad. This assessment is not based on a person's health over any specified period of time.
_Disability _
The definition of disability used in the 2021 Census is aligned with the definition of disability under the Equality Act (2010). A person is considered disabled if they self-report having a physical or mental health condition or illness that has lasted or is expected to last 12 months or more, and that this reduces their ability to carry out day-to-day activities.
Unpaid care
An unpaid carer may look after, give help or support to anyone who has long-term physical or mental ill-health conditions, illness or problems related to old age. This does not include any activities as part of paid employment. This help can be within or outside of the carer's household.
Abstract copyright UK Data Service and data collection copyright owner. This study was the fourth in a series of national surveys of ethnic minorities. The main objectives were:to describe the social and economic conditions of Britain's main ethnic minority groups, including their health, and to compare these with the social and economic conditions of the white majorityto assess changes over time through comparisons with other workto show how the position of ethnic minority groups is related to the social and ethnic compositions of the areas in which they liveto explore diversity among different ethnic minority groupsto describe perceptions and experience of racial discrimination and social harassment Main Topics: Topics covered include household structure, neighbourhoods and quality of housing, education, employment, health, racial harassment and discrimination, and ethnic identity. Multi-stage stratified random sample 1991 Census material was added to the dataset. Face-to-face interview Compilation or synthesis of existing material
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Dataset population: Persons
Ethnic group
Ethnic group classifies people according to their own perceived ethnic group and cultural background.
This topic contains ethnic group write-in responses without reference to the five broad ethnic group categories, e.g. all Irish people, irrespective of whether they are White, Mixed/multiple ethnic groups, Asian/Asian British, Black/African/Caribbean/Black British or Other ethnic group, are in the "Irish" response category. This topic was created as part of the commissioned table processing.
Religion
This is a person's current religion, or if the person does not have a religion, 'No religion'. No determination is made about whether a person was a practicing member of a religion. Unlike other census questions where missing answers are imputed, this question was voluntary and where no answer was provided, the response is categorised as 'Not stated'.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in England. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of England population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 68.50% of the total residents in England. Notably, the median household income for White households is $62,500. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $62,500.
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 England median household income by race. You can refer the same here
Abstract copyright UK Data Service and data collection copyright owner.The purpose of this survey was to study non-white people aged 15 and over, whose families originate from India, Pakistan and Bangladesh, or the East Indies, with reference to their housing, employment and educational characteristics, their awareness and experience of racial discrimination. Comparative data were also collected for white men aged 16 and over, using the same questionnaire but with questions omitted when not applicable. Main Topics: Attitudinal/Behavioural Questions Immigration: reasons; advantages of Britain/previous country; whether definite job arranged prior to arrival. Residence: number of rooms occupied; whether house was multi-occupied; amenities (whether shared); number of addresses in past five years. Tenure: 1. If owned: whether singly or jointly; mortgage/loan details; leasehold/freehold (date of expiry). 2. If rented: rent and rates details; council/private ownership; race of landlord. Council house tenants were asked how they obtained their housing. Reasons for leaving previous residence: A. Personal experience of mortgage/loan refusal, type of organisation which refused, year of application. B. Personal experience of refusal of rented accommodation, number of refusals, details of last refusal. In both A and B, respondents were asked to give the organisation's reasons for refusal and their personal opinion of reasons, with an explanation. Details of housing and financial facilities provided by the Council, entitlement/receipt of rent rebates and/or allowances, whether respondent has made an application to the council (length of time on waiting list). Occupation: hours worked per week, position, responsibility, qualifications, nature of firm, number of employees, source of information about job, promotion prospects, job satisfaction. In addition, respondents were asked whether they had visited the employment exchange or were receiving/had received benefits since 1964. Respondents were asked to relate experiences of unfair treatment with regard to promotion or application for jobs, and whether they thought there were firms giving equal opportunities to Asians and whites. Whether respondent believed employers discriminated against them - reasons. Details of previous refusals. Trade union membership and existence of unions at workplace. Whether unemployed women had ever considered working (reasons). Working women with children were asked about child care facilities (hours, cost, satisfaction, etc.) Asian women were asked whether religion or family custom restricted their lives in terms of work, going out, company. Desired change was explored. All respondents asked whether situation in Britain had improved for Asians over past five years - reasons. Knowledge of government bodies on race relations/Race Relations Board and its functions/Community Relations Commission and its functions was tested. Whether voted at previous general election. Whether on voting list. Background Variables Age, sex, place of birth, previous countries of residence, date of arrival in Britain, age on arrival in Britain. Number of persons in household, household status. Age finished full-time education, examination and qualification details, further study, school attended by children. Employment status, income, ownership of consumer durables. Residence: type, age, external conditions. Fluency in English, language of interview. Sampling area. Religion, church/mosque/temple attendance.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
These data are modelled using the OMOP Common Data Model v5.3.Correlated Data SourceNG tube vocabulariesGeneration RulesThe patient’s age should be between 18 and 100 at the moment of the visit.Ethnicity data is using 2021 census data in England and Wales (Census in England and Wales 2021) .Gender is equally distributed between Male and Female (50% each).Every person in the record has a link in procedure_occurrence with the concept “Checking the position of nasogastric tube using X-ray”2% of person records have a link in procedure_occurrence with the concept of “Plain chest X-ray”60% of visit_occurrence has visit concept “Inpatient Visit”, while 40% have “Emergency Room Visit”NotesVersion 0Generated by man-made rule/story generatorStructural correct, all tables linked with the relationshipWe used national ethnicity data to generate a realistic distribution (see below)2011 Race Census figure in England and WalesEthnic Group : Population(%)Asian or Asian British: Bangladeshi - 1.1Asian or Asian British: Chinese - 0.7Asian or Asian British: Indian - 3.1Asian or Asian British: Pakistani - 2.7Asian or Asian British: any other Asian background -1.6Black or African or Caribbean or Black British: African - 2.5Black or African or Caribbean or Black British: Caribbean - 1Black or African or Caribbean or Black British: other Black or African or Caribbean background - 0.5Mixed multiple ethnic groups: White and Asian - 0.8Mixed multiple ethnic groups: White and Black African - 0.4Mixed multiple ethnic groups: White and Black Caribbean - 0.9Mixed multiple ethnic groups: any other Mixed or multiple ethnic background - 0.8White: English or Welsh or Scottish or Northern Irish or British - 74.4White: Irish - 0.9White: Gypsy or Irish Traveller - 0.1White: any other White background - 6.4Other ethnic group: any other ethnic group - 1.6Other ethnic group: Arab - 0.6
Abstract copyright UK Data Service and data collection copyright owner. British General Election Study, 1997 : Ethnic Minority Survey The aims of the Ethnic Minority Survey are: to evaluate the extent to which ethnic minority voters are integrated into the electoral process; to evaluate whether, after taking into account their social background, members of the main ethnic minorities vote differently from each other and from their white counterparts; to examine whether the political attitudes of ethnic minority voters are significantly different from that of white voters; to examine whether members of ethnic minorities are influenced by different considerations than their white counterparts in deciding how to vote and to evaluate in particular, the importance of issues of race and immigration in voting behaviour of ethnic minority and white voters. Main Topics: The file contains data for 705 respondents from: an hour and ten minutes long face-to-face interview; a self-completion questionnaire; geographic information derived from the census; turn-out and electoral registration information derived from a check against the marked-up Electoral Registers. The respondents are partly a subset of the British General Election Study Cross-section Survey and partly an ethnic boost generated by a random screening survey. Standard Measures Self-completion Q3a,b,e,f,g,Q4a make up a standard BGES left-right scale; self-completion Q3c,d,Q4b-e make up a standard BGES libertarian-authoritarian scale. Multi-stage stratified random sample The sample was generated from three main sources: ethnic minority respondents who happened to be generated by the main study (samples A and B); a large-scale screening exercise in areas of high ethnic minority concentration (sample C); next-door screening at some sample points with high ethnic minority concentrations (sample D). Face-to-face interview Self-completion CAPI; Link to census data; check against marked-up electoral registers.
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 New Britain by race. It includes the population of New Britain across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of New Britain across relevant racial categories.
Key observations
The percent distribution of New Britain population by race (across all racial categories recognized by the U.S. Census Bureau): 82.88% are white, 4.57% are Black or African American, 0.35% are American Indian and Alaska Native, 5.78% are Asian, 0.39% are some other race and 6.02% 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 New Britain Population by Race & Ethnicity. You can refer the same here