This study contains selected electoral and demographic national data for nine nations in the 1950s and 1960s. The data were prepared for the Data Confrontation Seminar on the Use of Ecological Data in Comparative Cross-National Research held under the auspices of the Inter-university Consortium for Political and Social Research on April 1-18, 1969. One of the primary concerns of this international seminar was the need for cooperation in the development of data resources in order to facilitate exchange of data among individual scholars and research groups. Election returns for two or more national and/or local elections are provided for each of the nine nations, as well as ecological materials for at least two time points in the general period of the 1950s and 1960s. While each dataset was received at a single level of aggregation, the data have been further aggregated to at least a second level of aggregation. In most cases, the data can be supplied at the commune or municipality level and at the province or district level as well. Part 1 (Germany, Regierungsbezirke), Part 2 (Germany, Kreise), Part 3 (Germany, Lander), and Part 4 (Germany, Wahlkreise) contain data for all kreise, laender (states), administrative districts, and electoral districts for national elections in the period 1957-1969, and for state elections in the period 1946-1969, and ecological data from 1951 and 1961. Part 5 (France, Canton), and Part 6 (France, Departemente) contain data for the cantons and departements of two regions of France (West and Central) for the national elections of 1956, 1962, and 1967, and ecological data for the years 1954 and 1962. Data are provided for election returns for selected parties: Communist, Socialist, Radical, Federation de Gauche, and the Fifth Republic. Included are raw votes and percentage of total votes for each party. Ecological data provide information on total population, proportion of total population in rural areas, agriculture, industry, labor force, and middle class in 1954, as well as urbanization, crime rates, vital statistics, migration, housing, and the index of "comforts." Part 7 (Japan, Kanagawa Prefecture), Part 8 (Japan, House of Representatives Time Series), Part 9 (Japan, House of (Councilors (Time Series)), and Part 10 (Japan, Prefecture) contain data for the 46 prefectures for 15 national elections between 1949 and 1968, including data for all communities in the prefecture of Kanagawa for 13 national elections, returns for 8 House of Representatives' elections, 7 House of Councilors' elections, descriptive data from 4 national censuses, and ecological data for 1950, 1955, 1960, and 1965. Data are provided for total number of electorate, voters, valid votes, and votes cast by such groups as the Jiyu, Minshu, Kokkyo, Minji, Shakai, Kyosan, and Mushozoku for the Communist, Socialist, Conservative, Komei, and Independent parties for all the 46 prefectures. Population characteristics include age, sex, employment, marriage and divorce rates, total number of live births, deaths, households, suicides, Shintoists, Buddhists, and Christians, and labor union members, news media subscriptions, savings rate, and population density. Part 11 (India, Administrative Districts) and Part 12 (India, State) contain data for all administrative districts and all states and union territories for the national and state elections in 1952, 1957, 1962, 1965, and 1967, the 1958 legislative election, and ecological data from the national censuses of 1951 and 1961. Data are provided for total number of votes cast for the Congress, Communist, Jan Sangh, Kisan Mazdoor Praja, Socialist, Republican, Regional, and other parties, contesting candidates, electorate, valid votes, and the percentage of valid votes cast. Also included are votes cast for the Rightist, Christian Democratic, Center, Socialist, and Communist parties in the 1958 legislative election. Ecological data include total population, urban population, sex distribution, occupation, economically active population, education, literate population, and number of Buddhists, Christians, Hindus, Jainis, Moslems, Sikhs, and other religious groups. Part 13 (Norway, Province), and Part 14 (Norway, Commune) consist of the returns for four national elections in 1949, 1953, 1957, and 1961, and descriptive data from two national censuses. Data are provided for the total number

Abstract

The dataset is a relational dataset of 10,003,891 individuals (2,501,755 households), representing the entire population of an imaginary middle-income country. The dataset contains two data files: one with variables at the household level, the other one with variables at the individual level. It includes variables that are typically collected in population censuses (demography, education, occupation, dwelling characteristics, fertility, mortality, and migration) and in household surveys (household expenditure, anthropometric data for children, assets ownership). The data only includes ordinary households (no community households). The dataset was created using REaLTabFormer, a model that leverages deep learning methods. The dataset was created for the purpose of training and simulation and is not intended to be representative of any specific country.

A sample dataset of 8000 households was created out of this full-population dataset, and is also distributed as open data.

Geographic coverage

The dataset is a synthetic dataset for an imaginary country. It was created to represent the full national population of this country, by province and district (equivalent to admin1 and admin2 levels) and by urban/rural areas of residence.

Analysis unit

household, Individual

Universe

The dataset is a fully-synthetic dataset representative of the resident population of ordinary households for an imaginary middle-income country.

Kind of data

cen

Mode of data collection

other

Research instrument

The dataset is a synthetic dataset. Although the variables it contains are variables typically collected from sample surveys or population censuses, no questionnaire is available for this dataset. A "fake" questionnaire was however created for the sample dataset extracted from this dataset, to be used as training material.

Cleaning operations

The synthetic data generation process included a set of "validators" (consistency checks, based on which synthetic observation were assessed and rejected/replaced when needed). Also, some post-processing was applied to the data to result in the distributed data files.

Share of youth not in education, employment or training, total (% of youth population) in United States was reported at 11.19 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Share of youth not in education, employment or training, total - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

The US Census Bureau provides a large collection of data files, some of which are encoded separately or do not have an obvious means to integrate. Suppose that the files are located and need to be integrated to make some data-driven decisions using Census population estimates. The resultant files may be very useful to explore, but the user wants to get into visual representation and start considering things spatially and temporally. In this resource, the Jupyter notebook walks through a set of operations created to integrate Census population estimates with the known ESRI shapefile for the equivalent county-scales.

United States US: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data was reported at 17.370 % in 2012. This records a decrease from the previous number of 18.100 % for 2011. United States US: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data is updated yearly, averaging 17.935 % from Dec 2009 (Median) to 2012, with 4 observations. The data reached an all-time high of 18.100 % in 2011 and a record low of 17.370 % in 2012. United States US: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

The standard deviation is between brackets.a[47],b[27].Population statistics on simulated data for the five scenarios and reference values from published data.

Population not participating in education or training by main reason and sex

Abstract

The 2011 Population and Housing Census of Samoa was taken on the midnight of November the 7th 2011. It counted every person in the country on that night and collected a wide range of social, economic and demographic information about each individual and their housing status.

The information were used to develop statistical indicators to support national plannning and policy-making and also to monitor MDG indicators and all other related conventions. This included population growth rates, educational attainment, employment rates, fertility rates, mortality rates, internal movements, household access to water supply, electricity, sanitation, and many other information. The full report is available at SBS website: http://www.sbs.gov.ws under the section on Population statistics and demography.

Geographic coverage

National coverage Regions Districts Village Enumeration areas

Analysis unit

Private households Institutional households Individuals Women 15-49 Housing/Buildings

Universe

The PHC 2011 covered all de facto household members, institutional households such as boarding schools, hospitals, prison inmates and expatriates residing in Samoa for more than 3 months. The PHC excluded all tourists visiting Samoa during the enumeration period and all Samoans residing overseas.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable to a complete enumeration census.

Mode of data collection

Face-to-face [f2f]

Research instrument

Users' consultation seminars were conducted for three consecutive days (June 8th -10th, 2010) with financial support provided by the office of UNFPA in Suva via the Samoa Parliamentary Group for Population Development (SPGPD) annual programs. For the first time in census history, the SPGPD or members of parliament have become the target group of users to get involved in any census questionnaire consultations.

All government ministries and non-governmental organizations were invited to the consultation seminars and each was asked to make a presentation of data needs for consideration in the final census 2011 questionnaire. To avoid re-inventing the wheel in the compilation of the list of census questions for census 2011, the questionnaire from the census 2006 was reprinted and distributed to all participants and presenters to select questions that they would consider again for the census 2011 in addition to their new data needs. Users were also advised that any new question would need good justifications of how it links to national interests.

At the end of the three days seminar, all new questions were compiled for final selection by Samoa Bureau of Statistics. Not all the users' data needs have been included in the final 2011 census questionnaire due mainly to the cost involved and limited time for census enumeration. Therefore, the final selection of questions was purely based on the linkage of the data being requested to the list of statistical indicators in the 'Strategy for the Development of Samoa 2008-2012' (SDS) and the 'Millennium Development Goals' (MDGs) 2015. All data requests outside of the two frameworks were put aside to be integrated in other more appropriate survey activities by the bureau.

From July 2010-December 2010, the questionnaire was formatted using the In-Design CS4 software. It is important to note that the PHC 2011 was the first ever census using the scanning technology to process data from the census questionnaires as a replacement of the usual manual data entry process. The scanning was pilot tested in April 2011, before it was finally used for final census enumeration.

The questionnaire was designed using A3 paper size.

The Population questionnaire was administered in each household, which collected various information on household members including age, sex, citizenship, disability, orphanhood, marital status, residence (birth, usual, previous), religion, education and employment.

In the Population questionnaire, a special section was administered in each household for women age 15-49, which also asked information on their children ever born still living, died or living somewhere else. Mothers of children under one year were also asked whether their last born children were still living at the time of the census.

The Housing questionnaire was also administered in each household which collected information on the types of building the household lived, floor materials, wall materials, roof materials, land tenure, house tenure, water supply, drinking water, lighting, cooking fuel, toilet facility, telephone, computer, internet, refrigerator, radio, television and others.

Cleaning operations

Data editing was done in several stages. 1. Office manual editing and coding 2. Automatic scanning data entry edits 3. Visual verification questionnaire edits 3. Structure checking and completeness 4. Structure checks of the CSPro data files Editing program can be enquired at the Division of IT and Data Processing at email address: info.stats@sbs.gov.ws

Sampling error estimates

The census is a full-coverage of the population, therefore it is not a sample where sampling errors can be estimated.

Data appraisal

There was no post-enumeration in the census 2011. One of the normal practices by the bureau to validate the total population counts from all villages, districts and regions of Samoa in any census is the manual count of the population in all areas during the on-going census enumeration.That information is collected by the enumerators and field supervisors during the enumeration using the Enumerators and Supervisors control forms. At the end of the enumeration, the control forms which mainly contained the number of males and females per enumeration area will be collected and compiled by the Census and Survey division as the first preliminary count of the census. In the census 2011, the preliminary population counts were compiled and launched as the 'Village Directory 2011' report after 4 weeks from end of the enumeration period.

The significance of the Village Directory report is it helps to provide a qiuick overall picture of the population growth and population distribution in all villages of the country relative to previous censuses. Most important of all is that the preliminary count will provide the basis for a decision whether a post-enumeration is warrant or otherwise. If the preliminary country is close to the projected population then the post-enumeration is assumed not worth the cost because it is expensive and it will delay all other census processes. In the census 2011, the preliminary count arrived at 186,340 which was more than the projected population of 184,032 as depicted in the Statistical Abstract 2009. Therefore the decision was made that post-enumeration was not worth it.

Share of youth not in education, employment or training, total (% of youth population) in Finland was reported at 7.482 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Finland - Share of youth not in education, employment or training, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Share of youth not in education, employment or training, total (% of youth population) in Israel was reported at 14.94 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Israel - Share of youth not in education, employment or training, total - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

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Analysis of ‘Population not wanting to participate in education and training by main reason and educational attainment level’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://data.europa.eu/data/datasets/rljhvuz2pfmj3jxr02q on 30 September 2021.

--- No further description of dataset provided by original source ---

--- Original source retains full ownership of the source dataset ---

This collection provides data on labor force activity for the week prior to the survey. Comprehensive data are available on the employment status, occupation, and industry of persons aged 14 and over. Also shown are personal characteristics such as age, sex, race, marital status, veteran status, household relationship, educational background, and Spanish origin. The collection contains a supplement that includes data on skills and training that workers needed to obtain their current or last job, on-the-job training, skills used on the last job, and workers' perceptions of the adequacy of their skills. This supplement makes it possible to analyze changes in occupation and to assess the relative stability of employment in various industries and occupations. Questions were asked of all persons 15 years of age or older who were living in households and who were members of the experienced labor force, whether they were currently employed or not.

Population not participating in education or training by main reason and educational attainment level

Analysis of ‘Percentage of population pursuing academic education or training in the last four weeks by sex. EPA (API identifier: 45606)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/urn-ine-es-tabla-t3-341-45606 on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Table of INEBase Percentage of population pursuing academic education or training in the last four weeks by sex. Annual. National. Economically Active Population Survey

--- Original source retains full ownership of the source dataset ---

Population Services and Training Center (PSTC) Activity File

Population by sex, age and participation in education and training (last 4 weeks) (1 000)

Armenia AM: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data was reported at 25.142 % in 2021. This records a decrease from the previous number of 30.601 % for 2020. Armenia AM: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data is updated yearly, averaging 38.494 % from Dec 2007 (Median) to 2021, with 15 observations. The data reached an all-time high of 45.271 % in 2010 and a record low of 25.142 % in 2021. Armenia AM: Share of Youth Not in Education, Employment or Training: Female: % of Female Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Armenia – Table AM.World Bank.WDI: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.;International Labour Organization. “Labour Force Statistics database (LFS)” ILOSTAT. Accessed January 07, 2025. https://ilostat.ilo.org/data/.;Weighted average;

Survey on Adult Population Involvement in Learning Activities: Average number of training hours per participant in non-formal education activities by sex and age group. National.

Population wanting to participate in education and training, by main reason for not participating and age