The 1950 Census population schedules were created by the Bureau of the Census in an attempt to enumerate every person living in the United States on April 1, 1950, although some persons were missed. The 1950 census population schedules were digitized by the National Archives and Records Administration (NARA) and released publicly on April 1, 2022. The 1950 Census enumeration district maps contain maps of counties, cities, and other minor civil divisions that show enumeration districts, census tracts, and related boundaries and numbers used for each census. The coverage is nation wide and includes territorial areas. The 1950 Census enumeration district descriptions contain written descriptions of census districts, subdivisions, and enumeration districts.

"Website allows the public full access to the 1950 Census images, census maps and descriptions.

This data collection and its 1940 counterpart were assembled through a collaborative effort between the United States Bureau of the Census and the Center for Demography and Ecology of the University of Wisconsin. The 1940 and 1950 Census Public Use Sample Project was supported by The National Science Foundation under Grant SES-7704135. The collections contain a stratified 1-percent sample of households, with separate records for each household, for each \'sample line\' respondent, and for each person in the household. These records were encoded from microfilm copies of original handwritten enumeration schedules from the 1940 and 1950 Censuses of Population. The universe for the sample included all persons and households within the United States. Geographic identification of the location of the sampled households includes Census regions and divisions, States (except Alaska and Hawaii), Standard Metropolitan Areas (SMA\'s), and State Economic Areas (SEA\'s). The SMA\'s and SEA\'s are comparable for both the 1940 and 1950 Public Use Microdata Samples (PUMS). The data collections were constructed from and consist of 20 independently-drawn subsamples stored in 20 discrete physical files. Each of the 20 subsamples contains three record types (household, \'sample line\', and person). Both collections had both a complete-count and a sample component. Individuals selected for the sample component were asked a set of additional questions. Only households with a \'sample line\' person were included in the public use microdata sample. The collections also contain records of group quarters members who were also on the Census \'sample line\'. For the 1940 and 1950 collections, each household record contains variables describing the location and composition of the household. The \'sample line\' records for 1950 contain variables describing demographic characteristics such as nativity, marital status, number of children, veteran status, education, income, and occupation. The person records for 1950 contain such demographic variables as nativity, marital status, family membership, and occupation. Accompanying the data collections are code books which include an abstract, descriptions of sample design, processing procedures and file structure, a data dictionary (record layout), category code lists, and a glossary. The data collections are arranged by subsample with each subsample stored as a separate physical file of information. The 20 subsamples were selected randomly. Within each of the 20 subsamples, records are sequenced by State. Extracting all of the records for one State entails reading through all of the 20 physical files and selecting that State\'s records from each of the 20 subsamples. Record types are ordered within household (household characteristics first, \'sample line\' next, and person records last). The 1950 collection consists of a total of 2,844,458 data records: 461,130 household records, 461,130 \'sample line\' records, and 1,922,198 person records. Each record type has a logical record length of 133.;

1950 United States Census contains records from Montpelier, Washington, Vermont, USA by United States of America, Bureau of the Census; Washington, D.C.; Seventeenth Census of the United States, 1950; Record Group: Records of the Bureau of the Census, 1790-2007; Record Group Number: 29; Residence Date: 1950; Home in 1950: Montpelier, Washington, Vermont; Roll: 471; Sheet Number: 11; Enumeration District: 12-40 - .

This data collection contains a stratified 1-percent sample of households, with separate records for each household, each "sample line" respondent, and each person in the household. These records were encoded from microfilm copies of original handwritten enumeration schedules from the 1950 Census of Population. Geographic identification of the location of the sampled households includes Census regions and divisions, states (except Alaska and Hawaii), Standard Metropolitan Areas (SMAs), and State Economic Areas (SEAs). The data collection was constructed from and consists of 20 independently-drawn subsamples stored in 20 discrete physical files. The 1950 Census had both a complete-count and a sample component. Individuals selected for the sample component were asked a set of additional questions. Only households with a sample line person were included in the 1950 Public Use Microdata Sample. The collection also contains records of group quarters members who were also on the Census sample line. Each household record contains variables describing the location and composition of the household. The sample line records contain variables describing demographic characteristics such as nativity, marital status, number of children, veteran status, education, income, and occupation. The person records contain demographic variables such as nativity, marital status, family membership, and occupation. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08251.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

Two novel datasets—French 19th-century and U.S. 1950 Census records—to demonstrate our approach.

This metadata report documents tabular data sets consisting of items from the Census of Agriculture. These data are a subset of items from county-level data (including state totals) for the conterminous United States covering the census reporting years (every five years, with adjustments for 1978 and 1982) beginning with the 1950 Census of Agriculture and ending with the 2012 Census of Agriculture. Historical (1950-1997) data were extracted from digital files obtained through the Intra-university Consortium on Political and Social Research (ICPSR). More current (1997-2012) data were extracted from the National Agriculture Statistical Service (NASS) Census Query Tool for the census years of 1997, 2002, 2007, and 2012. Most census reports contain item values from the prior census for comparison. At times these values are updated or reweighted by the reporting agency; the Census Bureau prior to 1997 or NASS from 1997 on. Where available, the updated or reweighted data were used; otherwise, the original reported values were used. Changes in census item definitions and reporting as well as changes to county areas and names over the time span required a degree of manipulation on the data and county codes to make the data as comparable as possible over time. Not all of the census items are present for the entire 1950-2012 time span as certain items have been added since 1950 and when possible the items were derived from other items by subtracting or combining sub items. Specific changes and calculations are documented in the processing steps sections of this report. Other missing data occurs at the state and (or) county level due to census non-disclosure rules where small numbers of farms reporting an item have acres and (or) production values withheld to prevent identification of individual farms. In general, caution should be exercised when comparing current (2012) data with values reported in earlier censuses. While the 1974-2012 data are comparable, data prior to 1974 will have inflated farm counts and slightly inflated production amounts due to the differences in collection methods, primarily, the definition of a farm. Further discussion on comparability can be found the comparability section of the Supplemental Information element of this metadata report. Excluded from the tabular data are the District of Columbia, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the three county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. Data for independent cities of Virginia prior to 1959 have been included with their surrounding or adjacent county. Please refer to the Supplemental Information element for information on terminology, the Census of Agriculture, the Inter-university Consortium for Political and Social Research (ICPSR), table and variable structure, data comparability, all farms and economic class 1-5 farms, item calculations, increase of farms from 1974 to 1978, missing data and exclusion explanations, 1978 crop irregularities, pastureland irregularities, county alignment, definitions, and references. In addition to the metadata is an excel workbook (VariableKey.xlsx) with spreadsheets containing key spreadsheets for items and variables by category and a spreadsheet noting the presence or absence of entire variable data by year. Note: this dataset was updated on 2016-02-10 to populate omitted irrigation values for Miami-Dade County, Florida in 1997.

This polygon shapefile provides county or county-equivalent boundaries for the conterminous United States and was created specifically for use with the data tables published as Selected Items from the Census of Agriculture for the Conterminous United States, 1950-2012 (LaMotte, 2015). This data layer is a modified version of Historic Counties for the 2000 Census of Population and Housing produced by the National Historical Geographic Information System (NHGIS) project, which is identical to the U.S. Census Bureau TIGER/Line Census 2000 file, with the exception of added shorelines. Excluded from the CAO_STCOFIPS boundary layer are Broomfield County, Colorado, Menominee County, Wisconsin, and the independent cities of Virginia with the exception of the 3 county-equivalent cities of Chesapeake City, Suffolk, and Virginia Beach. The census of agriculture was not taken in the District of Columbia for 1959, but available data indicate few if any farms in that area, the polygon was left in place to preserve the areas of the surrounding counties. Baltimore City, Maryland was combined with Baltimore County and the St. Louis City, Missouri, was combined with St. Louis County. La Paz County, Arizona was combined with Yuma County, Arizona and Cibola County, New Mexico was combined with Valencia County, New Mexico. Minor county border changes were at a level of precision beyond the scope of the data collection. A major objective of the census data tabulation is to maintain a reasonable degree of comparability of agricultural data from census to census. The tabular data collection is from 14 different censuses where definitions and data collection techniques may change over time and while the data are mostly comparable, a degree of caution should be exercised when using the data in analysis procedures. While the data are at a county-level resolution, a regional approach is more appropriate than a county-by-county analysis. The main purpose of this layer is to provide a base to generate a county raster for the allocation of agricultural census values to specific (agricultural) pixels. Vector format is provided so the raster pixel size can be user designated. References cited: LaMotte, A.E., 2015, Selected items from the Census of Agriculture at the county level for the conterminous United States, 1950-2012: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7H13016. National Historical Geographic Information System, Minnesota Population Center, 2004, Historic counties for the 2000 census of population and housing: Minneapolis, MN, University of Minnesota, accessed 03/18/2013 at http://nhgis.org

This product provides tabular data from the U.S. Department of Agriculture (USDA) Census of Agriculture for selected items for the period 1950-2017 for counties in the conterminous United States. Data from 1950-2012 are taken from LaMotte (2015) and 2017 data are retrieved from the USDA QuickStats online tool. Data which are withheld in the Census of Agriculture are filled with estimates. The data include crop production values for 12 commodities (for example, corn in bushels), land use values for 7 land use types (for example, acres of total cropland), and 9 values for livestock types (for example, number of hogs and pigs). The data are largely intended as a 2017 update to the LaMotte dataset for items of research interest. LaMotte, A.E., 2015, Selected items from the Census of Agriculture at the county level for the conterminous United States, 1950-2012: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7H13016.

The study of social class and corresponding measurement schemes has evolved separately in Europe and the US. On both continents a standardized occupational coding system exists that can be transferred into a wide scala of measures of socioeconomic status. This dataset contains a crosswalk between the two standardized historical occupational coding schemes: HISCO and Occ1950.

The Historical International Standardized Classification of Occupations (HISCO) is the European standard for occupational coding and can be used to generate social class schemes, such as HISCLASS, SOCPO, and HISCAM. The U.S. Bureau of the Census' 1950 standard (Occ1950) is the U.S. standard for occupational coding and can be used to generate social class schemes, like NPBOSS, OCCSCORE, PRESGL, and SEI. With the crosswalk, HISCO can be converted to the American class coding schemes and Occ1950 into the European class coding schemes.

Occupational categories were linked between HISCO and Occ1950 on the underlying occupations. Both HISCO and Occ1950 consist of multiple layers of occupational groups. HISCO is divided in 7 major, 76 minor, 296 unit, and 1,675 micro groups, which roughly correspond with: social classes, sectors, occupational groups, and occupational subgroups. Occ1950 on the other hand is divided in 10 social classes and 269 occupational groups. HISCO’s micro groups and Occ1950’s occupational subgroups are based on a well-documented number of occupations, which can easily be compared and matched between both occupational coding schemes.

In the translation from HISCO to Occ1950 1,675 occupational categories were collapsed into 229 Occ1950 unique occupational groups. Although 40 occupational groups in Occ1950 could not be retrieved from HISCO, all occupations were successfully attributed to the right social class. Vice versa, 269 occupational groups in Occ1950 were recoded into 227 HISCO micro groups. Together these 227 unique codes are well-spread over the different branches of the HISCO tree, as they cover most of the unit groups.

#Please note that this is not the crosswalk from Occ1950 to the intermediate HISCO used by the NAPP project, also known as OCCHISCO or NAPPHISCO. This crosswalk can be retrieved from: https://github.com/rlzijdeman/o-clack/tree/master/crosswalks/occhisco_to_hisco

#HISCO is the European standard for occupational coding and can be used to generate HISCLASS, SOCPO and HISCAM classifications. The necessary conversion table has been made available by Mandemakers et al. and is available on: https://socialhistory.org/en/hsn/hsn-standardized-hisco-coded-and-classified-occupational-titles-release-201301?language=en

#Occ1950 is the US standard for occupational coding. The occupational coding system is based on the US Census of 1950 and can be transferred into OCCSCORE, PRESGL, SEI, and Nam-Powers-Boyd. Crosswalks are available on request: https://usa.ipums.org/usa/vols_4_5_index.shtml

US Census Projection: Population: Mid Year data was reported at 204,461,198.000 Person in 2100. This records a decrease from the previous number of 205,458,306.000 Person for 2099. US Census Projection: Population: Mid Year data is updated yearly, averaging 211,450,473.000 Person from Jun 1950 (Median) to 2100, with 151 observations. The data reached an all-time high of 238,504,547.000 Person in 2052 and a record low of 53,443,075.000 Person in 1950. US Census Projection: Population: Mid Year data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s Brazil – Table BR.GAB038: Population: Projection: US Census Bureau.

Venezuela Population: Census: Age 85-89 data was reported at 104,141.000 Person in 2011. This records an increase from the previous number of 11,873.000 Person for 1950. Venezuela Population: Census: Age 85-89 data is updated yearly, averaging 58,007.000 Person from Dec 1950 (Median) to 2011, with 2 observations. The data reached an all-time high of 104,141.000 Person in 2011 and a record low of 11,873.000 Person in 1950. Venezuela Population: Census: Age 85-89 data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Venezuela – Table VE.G001: Population.

Venezuela Population: Census: Age >=90 data was reported at 55,328.000 Person in 2011. This records an increase from the previous number of 8,079.000 Person for 1950. Venezuela Population: Census: Age >=90 data is updated yearly, averaging 31,703.500 Person from Dec 1950 (Median) to 2011, with 2 observations. The data reached an all-time high of 55,328.000 Person in 2011 and a record low of 8,079.000 Person in 1950. Venezuela Population: Census: Age >=90 data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Venezuela – Table VE.G001: Population.

This dataset is a digital compilation of the "Population of States and Counties of the United States: 1790-1990" publication and the "Census U.S. Decennial County Population Data, 1900-1990" resource. It provides population data for U.S. states and counties from the years 1790 to 1950. In addition to the county and state population figures, the dataset also includes the total U.S. population and state population data, as presented in the "Population of States and Counties of the United States: 1790-1990" publication.

Unadjusted decennial census data from 1950-2000 and projected figures from 2010-2040: summary table of New York City population numbers and percentage share by Borough, including school-age (5 to 17), 65 and Over, and total population.

This product provides tabular estimates of kilograms of nitrogen and phosphorus from a) fertilizer, and b) manure, for counties in the conterminous United States for the period 1950-2017. Data are generated for approximate five-year periods over the time, coinciding with U.S. Department of Agriculture Census of Agriculture census years. This data release also includes a model archive suitable for recreating the 2017 fertilizer estimates.

Venezuela Population: Census: Male: Age >=90 data was reported at 19,807.000 Person in 2011. This records an increase from the previous number of 4,678.000 Person for 1950. Venezuela Population: Census: Male: Age >=90 data is updated yearly, averaging 12,242.500 Person from Dec 1950 (Median) to 2011, with 2 observations. The data reached an all-time high of 19,807.000 Person in 2011 and a record low of 4,678.000 Person in 1950. Venezuela Population: Census: Male: Age >=90 data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Venezuela – Table VE.G001: Population.

In 2023, about 17.7 percent of the American population was 65 years old or over; an increase from the last few years and a figure which is expected to reach 22.8 percent by 2050. This is a significant increase from 1950, when only eight percent of the population was 65 or over. A rapidly aging population In recent years, the aging population of the United States has come into focus as a cause for concern, as the nature of work and retirement is expected to change to keep up. If a population is expected to live longer than the generations before, the economy will have to change as well to fulfill the needs of the citizens. In addition, the birth rate in the U.S. has been falling over the last 20 years, meaning that there are not as many young people to replace the individuals leaving the workforce. The future population It’s not only the American population that is aging -- the global population is, too. By 2025, the median age of the global workforce is expected to be 39.6 years, up from 33.8 years in 1990. Additionally, it is projected that there will be over three million people worldwide aged 100 years and over by 2050.

This dataset is made up of images containing handwritten 3-digit occupation codes from the Norwegian population census of 1950. The occupation codes were added to the census sheets by Statistics Norway after the census was concluded for the purpose of creating aggregated occupational statistics for the entire population. The coding standard used in the 1950 census is, according to Statistics Norway’s official publications (https://www.ssb.no/historisk-statistikk/folketellinger/folketellingen-1950, booklet 4, page 81), very similar to the standards used in the census for 1920. Cf. the 13th booklet published for the 1920 census (https://www.ssb.no/historisk-statistikk/folketellinger/folketellingen-1920, note that this booklet is only available in Norwegian). In short, an occupation code is a 3-digit number that corresponds to a given occupation or type of occupation. According to the official list of occupation codes provided by Statistics Norway there are 339 unique codes. These are not all necessarily sequential or hierarchical in general, but some subgroupings are. This list can be found under Files. It is also worth noting that these images were extracted from the original census sheet images algorithmically. This process was not flawless and lead to additional images being extracted, these can contain written occupation titles or be left entirely blank. The dataset consists of 90,000 unique images, and 9,000 images that were randomly selected and copied from the unique images. These were all used for a research project (link to preprint article: https://doi.org/10.48550/arXiv.2306.16126) where we (author list can be found in preprint) tried to find a more efficient way of reviewing and correcting classification results from a Machine Learning model, where the results did not pass a pre-set confidence threshold. This was a follow-up to our previous article where we describe the initial project and creating of our model in more detail, if it is of interest (“Lessons Learned Developing and Using a Machine Learning Model to Automatically Transcribe 2.3 Million Handwritten Occupation Codes”, https://doi.org/10.51964/hlcs11331).

Mexico Population: Census: 45 to 49 Yrs Old data was reported at 6,814.143 Person th in 2015. This records an increase from the previous number of 5,928.730 Person th for 2010. Mexico Population: Census: 45 to 49 Yrs Old data is updated yearly, averaging 3,612.452 Person th from Dec 1950 (Median) to 2015, with 9 observations. The data reached an all-time high of 6,814.143 Person th in 2015 and a record low of 1,073.549 Person th in 1950. Mexico Population: Census: 45 to 49 Yrs Old data remains active status in CEIC and is reported by National Institute of Statistics and Geography. The data is categorized under Global Database’s Mexico – Table MX.G002: Population: Census.