This statistic looks at which socio-economic demographics retailers target in the United Kingdom in 2016. According to the survey, 81 percent of retailers focus on the AB social-economic group (upper middle and middle classes) while only one percent focus on groups DE (working and non-working classes).

During the observed period, the level of extreme poverty has increased in the social groups mentioned. However, the group most at risk of extreme poverty in Poland were households living mainly from so-called unearned sources and farmers.

This spread sheet shows ABS geographic standards from 2006 across Australia and the % of the 15-64 year old population within each Socio-Economic Indexes for Individuals (SEIFI) IRSD group. The data used to create this information was the same as used in the research paper “Socio-Economic Indexes for Areas: Getting a handle on individual diversity within areas” by Phillip Wise and Rosalynn Mathews. It is advised that this paper is read to further develop an understanding of the concepts and …Show full descriptionThis spread sheet shows ABS geographic standards from 2006 across Australia and the % of the 15-64 year old population within each Socio-Economic Indexes for Individuals (SEIFI) IRSD group. The data used to create this information was the same as used in the research paper “Socio-Economic Indexes for Areas: Getting a handle on individual diversity within areas” by Phillip Wise and Rosalynn Mathews. It is advised that this paper is read to further develop an understanding of the concepts and caveats associated with the analytical output contained in the spreadsheet. Group 1 – Approx. most disadvantage 20% of the 15-64 year old population Group 2 – Approx. second most disadvantaged 20% of the 15- 64 population Group 3 – Approx. second least disadvantaged 30% of the 15-64 year old population Group 4 – Approx. least disadvantaged 30% of the 15-64 year old population

Abstract copyright UK Data Service and data collection copyright owner.

The Great Britain Historical Database has been assembled as part of the ongoing Great Britain Historical GIS Project. The project aims to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain at sub-county scales. Further information about the project is available on A Vision of Britain webpages, where users can browse the database's documentation system online.

These data were originally collected by the Censuses of Population for England and Wales, and for Scotland. They were computerised by the Great Britain Historical GIS Project and its collaborators. They form part of the Great Britain Historical Database, which contains a wide range of geographically-located statistics, selected to trace the emergence of the north-south divide in Britain and to provide a synoptic view of the human geography of Britain, generally at sub-county scales.

The first census report to tabulate social class was 1951, but this collection also includes a table from the Registrar-General's 1931 Decennial Supplement which drew on census occupational data to tabulate social class by region. In 1961 and 1971 the census used a more detailed classification of Socio-Economic Groups, from which the five Social Classes are a simplification.

This is a new edition. Data from the Census of Scotland have been added for 1951, 1961 and 1971. Wherever possible, ID numbers have been added for counties and districts which match those used in the digital boundary data created by the GBH GIS, greatly simplifying mapping.

Main Topics:

Social Class Statistics from the 1931 Decennial Supplement for regions.

Social Class Statistics from the 1951, 1961 and 1971 Censuses (including Scotland), mainly for men and type of occupation.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

Licensed under: Creative Commons Attribution 4.0

This dataset presents the percentage of the 15-64 year old population within each Socio-Economic Indexes for Individuals (SEIFI) Index of Relative Socio-economic Disadvantage (IRSD) group. The data has been aggregated to the 2006 Census Collection Districts (CD). This datasets presents the IRSD groups to 10 categories, where group 1 is the 10% most disadvantaged 15-64 year old population and group 10 presents the most advantaged 10% of 15-64 year old population. For more information please visit the ACT Government Data Portal.

Over the period from 2010 to 2020, profile creation increased among all socio-economic group. During the survey in 2020, it was revealed that 83 percent of responding individuals from social grade C1 reported setting up their personal profile on a social networking platform.

This file contains original variables from Theme 9 Social Class from Census 2011 and a series of additional variables produced by AIRO such as percentage rates, ratios etc. The file includes data on Social Class, Socio-Economic Group of Persons and Persons in Private Households for the 18,488 Small Areas in the Republic of Ireland.

This dataset presents the percentage of the 15-64 year old population within each Socio-Economic Indexes for Individuals (SEIFI) Index of Relative Socio-economic Disadvantage (IRSD) group. The data has been aggregated to the 2006 Census Collection Districts (CD).

This datasets presents the IRSD groups to 4 categories, where:

• Group 1 – Approx. most disadvantage 20% of the 15-64 year old population.

• Group 2 – Approx. second most disadvantaged 20% of the 15- 64 population.

• Group 3 – Approx. second least disadvantaged 30% of the 15-64 year old population.

• Group 4 – Approx. least disadvantaged 30% of the 15-64 year old population. For more information please visit the ACT Government Data Portal.

Please note:

• AURIN has spatially enabled the original data.

Persons in private households by socio-economic group of reference person by Province. (Census 2022 Theme 9 Table 2 )Census 2022 table 9.2 is persons in private households by socio-economic group of reference person. Attributes include breakdown of households by socio-economic group of reference person, number of households and number of persons. Census 2022 theme 9 is Social Class and Socio-Economic Group.The methodology has changed for SOC and SEG so comparisons cannot be made with 2016 data. See Background Notes - CSO - Central Statistics Officehttps://www.cso.ie/en/releasesandpublications/ep/p-cpp7/census2022profile7-employmentoccupationsandcommuting/backgroundnotes/ Ireland is divided into four provinces - Leinster, Ulster, Munster and Connacht. They do not have any administrative functions and they are relevant for a number of historical, cultural and sporting reasons. The borders of the provinces coincide with the boundaries of counties. Three of the nine counties in Ulster are within the jurisdiction of the State.Coordinate reference system: Irish Transverse Mercator (EPSG 2157). These boundaries are based on 20m generalised boundaries sourced from Tailte Éireann Open Data Portal. Provinces - National Statutory Boundaries - 2019This dataset is provided by Tailte Éireann

Number of Private Households by Socio-economic Group of Reference Person 리소스 XLSX en XLSX 다운로드 Number of Private Households by Socio-economic Group of Reference Person

This study contains selected demographic, social, economic, public policy, and political comparative data for Switzerland, Canada, France, and Mexico for the decades of 1900-1960. Each dataset presents comparable data at the province or district level for each decade in the period. Various derived measures, such as percentages, ratios, and indices, constitute the bulk of these datasets. Data for Switzerland contain information for all cantons for each decennial year from 1900 to 1960. Variables describe population characteristics, such as the age of men and women, county and commune of origin, ratio of foreigners to Swiss, percentage of the population from other countries such as Germany, Austria and Lichtenstein, Italy, and France, the percentage of the population that were Protestants, Catholics, and Jews, births, deaths, infant mortality rates, persons per household, population density, the percentage of urban and agricultural population, marital status, marriages, divorces, professions, factory workers, and primary, secondary, and university students. Economic variables provide information on the number of corporations, factory workers, economic status, cultivated land, taxation and tax revenues, canton revenues and expenditures, federal subsidies, bankruptcies, bank account deposits, and taxable assets. Additional variables provide political information, such as national referenda returns, party votes cast in National Council elections, and seats in the cantonal legislature held by political groups such as the Peasants, Socialists, Democrats, Catholics, Radicals, and others. Data for Canada provide information for all provinces for the decades 1900-1960 on population characteristics, such as national origin, the net internal migration per 1,000 of native population, population density per square mile, the percentage of owner-occupied dwellings, the percentage of urban population, the percentage of change in population from preceding censuses, the percentage of illiterate population aged 5 years and older, and the median years of schooling. Economic variables provide information on per capita personal income, total provincial revenue and expenditure per capita, the percentage of the labor force employed in manufacturing and in agriculture, the average number of employees per manufacturing establishment, assessed value of real property per capita, the average number of acres per farm, highway and rural road mileage, transportation and communication, the number of telephones per 100 population, and the number of motor vehicles registered per 1,000 population. Additional variables on elections and votes are supplied as well. Data for France provide information for all departements for all legislative elections since 1936, the two presidential elections of 1965 and 1969, and several referenda held in the period since 1958. Social and economic data are provided for the years 1946, 1954, and 1962, while various policy data are presented for the period 1959-1962. Variables provide information on population characteristics, such as the percentages of population by age group, foreign-born, bachelors aged 20 to 59, divorced men aged 25 and older, elementary school students in private schools, elementary school students per million population from 1966 to 1967, the number of persons in household in 1962, infant mortality rates per million births, and the number of priests per 10,000 population in 1946. Economic variables focus on the Gross National Product (GNP), the revenue per capita per household, personal income per capita, income tax, the percentage of active population in industry, construction and public works, transportation, hotels, public administration, and other jobs, the percentage of skilled and unskilled industrial workers, the number of doctors per 10,000 population, the number of agricultural cooperatives in 1946, the average hectares per farm, the percentage of farms cultivated by the owner, tenants, and sharecroppers, the number of workhorses, cows, and oxen per 100 hectares of farmland in 1946, and the percentages of automobiles per 1,000 population, radios per 100 homes, and cinema seats per 1,000 population. Data are also provided on the percentage of Communists (PCF), Socialists, Radical Socialists, Conservatives, Gaullists, Moderates, Poujadists, Independents, Turnouts, and other political groups and p

An information system based on data from the healthcare sector and related areas. The online portal gives researchers the opportunity to research various health topics including population, socio-economic factors, health insurance, health laws.

• Laws

• Population

  • Births
  • Deaths
  • Population Numbers
  • other

• Pregnancy, Births

• Terminations of Pregnancy

• Households, Families, Living Communities

• Social Conditions

  • Education
  • Habitation
  • Employment
  • Unemployment
  • Poverty and Disparity
  • Single parent
  • Income
  • Social Welfare
  • other

• Training of the Health Personnel

• Economy

• Research

• Private Health Insurance

• Statutory Health Insurance

  • Statutory Health Insurance: Income, Expenditure
  • Statutory Health Insurance: Members, Insured Persons
  • Statutory Health Insurance: Services
  • Statutory Health Insurance: Services (Pharmaceuticals)
  • Statutory Health Insurance: other

• Nursing Care Insurance

• Pension Insurance

  • Insured Persons
  • Rehabilitation Services
  • Pensions because of old age
  • Ppensions because of diminution of ability to wrk
  • Pensions because of death (widow/widower pensions)
  • other

• Accident Insurance, employers' liability insurance association

This survey collected data to generate a comprehensive review of the economic and policy status of the recreational for-hire sector in the U.S. Gulf of Mexico, including charter, head, and guide boats. The survey created a socioeconomic dataset that can be used to analyze future economic, environmental, and policy questions, including those related to natural disturbances and the ongoing regulation of resource utilization in the Gulf. The specific project objectives included a) collecting economic, social, and policy data for all segments of the for-hire sector b) identifying groups of respondents with relatively homogeneous characteristics, thereby defining operational classes that may be the focus of targeted, management-based economic and policy analysis and c) constructing costs, earnings, and attitudinal profiles by operational class and state/region. The survey was conducted by mail, internet, and in-person interviews in 2010.

A 2023 survey among internet users in the United Kingdom (UK) found that users belong to the socio-economic group B (middle middle class) accounted for 31 percent of broad online users, who used the internet for nine to 13 types of online activities.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household, enterprise

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Persons without any normal residence, foreign nationals, and people in barracks of military and para-military forces, orphanages, rescue homes, ashram and vagrant houses are not covered by survey.

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen will constitute a household. The members of a household may or may not be related by blood to one another.

Universe

All population in India, except for foreigners, the homeless, or people in barracks of military and para-military forces, orphanages, rescue homes, ashram, and vagrant houses.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Two-stage, stratified samples drawn by the country, coupled with rotation sampling scheme for the central sample. (1) Stage 1: In the central sample, 10,384 first stage units (rural and urban combined) were selected from stratified states in proportion to poluation. Among them, 3,900 of which were revisted. (2) Stage 2: households and enterprises were selected from second-stage strata(hamlet-groups or sub-blocks) by circular systematic sampling with equal probability. (3) Under the rotation sampling scheme which was adopted for the first time in the National Sample Survey, 50% of the sample first stage units in the central sample were revisited in the subsequent three-month period. In state samples, the first stage units were only visited once.

SAMPLE UNIT: Household

SAMPLE FRACTION: .07%

SAMPLE SIZE (person records): 596,688

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 8 sections: 1) identification of sample household, 2) household characteristics, 3) demographic and migration particulars, 4) usual principal activity, 5) subsidiary activity, 6) current work activity during the preceding week, 5) follow-up questions for the unemployed, 6) availability for work to working persons, 7) job change of working persons, and 8) questions for females.

Response rate

COVERAGE: 100% of the Indian Union excepting (1) Ladakh and Kargil districts of Jammu and Kashmir, (2) interior villages of Nagaland situated beyond 5 kms. of a bus route, and (3) villages of Andaman and Nicobar Islands remaining inaccessible throughout the year. Also excluded were all the uninhabited villages according to 1991 census.

SAP2011T9T2CTY - Number of private households by socio-economic group of reference person. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Number of private households by socio-economic group of reference person...

This feature layer was created using Census 2016 data produced by the Central Statistics Office (CSO) and Municipal Districts boundary data (generalised to 50m) produced by Tailte Éireann. The layer represents Census 2016 theme 9.2, persons in private households by socio-economic group of reference person. Attributes include breakdown of households by socio-economic group of reference person, number of households and number of persons (e.g. E Manual skilled (No. of households), B Higher professional (No. of persons)). Census 2016 theme 9 represents Social Class and Socio-Economic Group. The Census is carried out every five years by the CSO to determine an account of every person in Ireland. The results provide information on a range of themes, such as, population, housing and education. The data were sourced from the CSO.The Municipal District Boundary dataset generalised to 50m has been generated from the Tailte Éireann National Statutory Boundary dataset.

Created as part of the MMO report Maximising the Socio-Economic Impacts of Marine Planning for English Coastal Communities (planning team). Differentiates between different types of coastal areas on the basis of their socio-economic characteristics.

Further information on coastal typologies can be found on page 97 of the report.

The RVI/CVI database is derived from the CanEcumene 3.0 GDB (Eddy, et. al. 2023) using a selection of socio-economic variables identified in Eddy and Dort (2011) that aim to capture the overall state of socio-economic conditions of communities as ‘human habitats’. This dataset was developed primarily for application in mapping socio-economic conditions of communities and regions for environmental and natural resource management, climate change adaptation, Impact Assessments (IAs) and Regional Assessments (RAs), and Cumulative Effects Assessment (CEA). The RVI/CVI is comprised of five sub-indicators: 1) population change, 2) age structure, 3) education levels, 4) employment levels, and 5) real estate values. Index values are based on percentile ranks of each sub-indicator, and averaged for each community, and for three ranked groups: 1) all of Canada, 2) by province, and 3) by population size. The data covers the Census periods of 2001, 2006, 2011 (NHS), 2016, and 2021. The index is mapped in two ways: 1) as ‘points’ for individual communities (CVI), and 2) as ‘rasters’ for spatial interpolation of point data (RVI). These formats provide an alternative spatial framework to conventional StatsCan CSD framework. (For more information on this approach see Eddy, et. al. 2020). ============================================================================================ Eddy, B.G., Muggridge, M., LeBlanc, R., Osmond, J., Kean, C., and Boyd, E. 2023. The CanEcumene 3.0 GIS Database. Federal Geospatial Platform (FGP), Natural Resources Canada. https://gcgeo.gc.ca/viz/index-en.html?keys=draft-3f599fcb-8d77-4dbb-8b1e-d3f27f932a4b Eddy B.G., Muggridge M, LeBlanc R, Osmond J, Kean C, Boyd E. 2020. An Ecological Approach for Mapping Socio-Economic Data in Support of Ecosystems Analysis: Examples in Mapping Canada’s Forest Ecumene. One Ecosystem 5: e55881. https://doi.org/10.3897/oneeco.5.e55881 Eddy, B.G.; Dort, A. 2011. Integrating Socio-Economic Data for Integrated Land Management (ILM): Examples from the Humber River Basin, western Newfoundland. Geomatica, Vol. 65, No. 3, p. 283-291. doi:10.5623/cig2011-044.