The 119th Congressional Districts dataset reflects boundaries from January 03, 2025 from the United States Census Bureau (USCB), and the attributes are updated every Sunday from the United States House of Representatives and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Information for each member of Congress is appended to the Census Congressional District shapefile using information from the Office of the Clerk, U.S. House of Representatives' website https://clerk.house.gov/xml/lists/MemberData.xml and its corresponding XML file. Congressional districts are the 435 areas from which people are elected to the U.S. House of Representatives. This dataset also includes 9 geographies for non-voting at large delegate districts, resident commissioner districts, and congressional districts that are not defined. After the apportionment of congressional seats among the states based on census population counts, each state is responsible for establishing congressional districts for the purpose of electing representatives. Each congressional district is to be as equal in population to all other congressional districts in a state as practicable. The 119th Congress is seated from January 3, 2025 through January 3, 2027. In Connecticut, Illinois, and New Hampshire, the Redistricting Data Program (RDP) participant did not define the CDs to cover all of the state or state equivalent area. In these areas with no CDs defined, the code "ZZ" has been assigned, which is treated as a single CD for purposes of data presentation. The TIGER/Line shapefiles for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) each contain a single record for the non-voting delegate district in these areas. The boundaries of all other congressional districts reflect information provided to the Census Bureau by the states by May 31, 2024. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529006

The Voter Participation indicator presents voter turnout in Champaign County as a percentage, calculated using two different methods.

In the first method, the voter turnout percentage is calculated using the number of ballots cast compared to the total population in the county that is eligible to vote. In the second method, the voter turnout percentage is calculated using the number of ballots cast compared to the number of registered voters in the county.

Since both methods are in use by other agencies, and since there are real differences in the figures that both methods return, we have provided the voter participation rate for Champaign County using each method.

Voter participation is a solid illustration of a community’s engagement in the political process at the federal and state levels. One can infer a high level of political engagement from high voter participation rates.

The voter participation rate calculated using the total eligible population is consistently lower than the voter participation rate calculated using the number of registered voters, since the number of registered voters is smaller than the total eligible population.

There are consistent trends in both sets of data: the voter participation rate, no matter how it is calculated, shows large spikes in presidential election years (e.g., 2008, 2012, 2016, 2020) and smaller spikes in intermediary even years (e.g., 2010, 2014, 2018, 2022). The lowest levels of voter participation can be seen in odd years (e.g., 2015, 2017, 2019, 2021, 2023).

This data primarily comes from the election results resources on the Champaign County Clerk website. Election results resources from Champaign County include the number of ballots cast and the number of registered voters. The results are published frequently, following each election.

Data on the total eligible population for Champaign County was sourced from the U.S. Census Bureau, using American Community Survey (ACS) 1-Year Estimates for each year starting in 2005, when the American Community Survey was created. The estimates are released annually by the Census Bureau.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because this data is not available for Champaign County, the eligible voting population for 2020 is not included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Population by Sex and Population Under 18 Years by Age.

Sources: Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (10 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (5 October 2023).; Champaign County Clerk Historical Election Data; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (7 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using data.census.gov; (8 June 2021).; Champaign County Clerk Election History; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (13 May 2019).; U.S. Census Bureau; American Community Survey, American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (6 March 2017).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey 2012 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B05003; generated by CCRPC staff; using American FactFinder; (15 March 2016).

Abstract

Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation.The census plays an essential role in public administration. The results are used to ensure: • equity in distribution of government services • distributing and allocating government funds among various regions and districts for education and health services • delineating electoral districts at national and local levels, and • measuring the impact of industrial development, to name a few The census also provides the benchmark for all surveys conducted by the national statistical office. Without the sampling frame derived from the census, the national statistical system would face difficulties in providing reliable official statistics for use by government and the public. Census also provides information on small areas and population groups with minimum sampling errors. This is important, for example, in planning the location of a school or clinic. Census information is also invaluable for use in the private sector for activities such as business planning and market analyses. The information is used as a benchmark in research and analysis.

Census 2011 was the third democratic census to be conducted in South Africa. Census 2011 specific objectives included: - To provide statistics on population, demographic, social, economic and housing characteristics; - To provide a base for the selection of a new sampling frame; - To provide data at lowest geographical level; and - To provide a primary base for the mid-year projections.

Geographic coverage

National

Analysis unit

Households, Individuals

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

About the Questionnaire : Much emphasis has been placed on the need for a population census to help government direct its development programmes, but less has been written about how the census questionnaire is compiled. The main focus of a population and housing census is to take stock and produce a total count of the population without omission or duplication. Another major focus is to be able to provide accurate demographic and socio-economic characteristics pertaining to each individual enumerated. Apart from individuals, the focus is on collecting accurate data on housing characteristics and services.A population and housing census provides data needed to facilitate informed decision-making as far as policy formulation and implementation are concerned, as well as to monitor and evaluate their programmes at the smallest area level possible. It is therefore important that Statistics South Africa collects statistical data that comply with the United Nations recommendations and other relevant stakeholder needs.

The United Nations underscores the following factors in determining the selection of topics to be investigated in population censuses: a) The needs of a broad range of data users in the country; b) Achievement of the maximum degree of international comparability, both within regions and on a worldwide basis; c) The probable willingness and ability of the public to give adequate information on the topics; and d) The total national resources available for conducting a census.

In addition, the UN stipulates that census-takers should avoid collecting information that is no longer required simply because it was traditionally collected in the past, but rather focus on key demographic, social and socio-economic variables.It becomes necessary, therefore, in consultation with a broad range of users of census data, to review periodically the topics traditionally investigated and to re-evaluate the need for the series to which they contribute, particularly in the light of new data needs and alternative data sources that may have become available for investigating topics formerly covered in the population census. It was against this background that Statistics South Africa conducted user consultations in 2008 after the release of some of the Community Survey products. However, some groundwork in relation to core questions recommended by all countries in Africa has been done. In line with users' meetings, the crucial demands of the Millennium Development Goals (MDGs) should also be met. It is also imperative that Stats SA meet the demands of the users that require small area data.

Accuracy of data depends on a well-designed questionnaire that is short and to the point. The interview to complete the questionnaire should not take longer than 18 minutes per household. Accuracy also depends on the diligence of the enumerator and honesty of the respondent.On the other hand, disadvantaged populations, owing to their small numbers, are best covered in the census and not in household sample surveys.Variables such as employment/unemployment, religion, income, and language are more accurately covered in household surveys than in censuses.Users'/stakeholders' input in terms of providing information in the planning phase of the census is crucial in making it a success. However, the information provided should be within the scope of the census.

1. The Household Questionnaire is divided into the following sections:
2. Household identification particulars

3. Individual particulars Section A: Demographics Section B: Migration Section C: General Health and Functioning Section D: Parental Survival and Income Section E: Education Section F: Employment Section G: Fertility (Women 12-50 Years Listed) Section H: Housing, Household Goods and Services and Agricultural Activities Section I: Mortality in the Last 12 Months The Household Questionnaire is available in Afrikaans; English; isiZulu; IsiNdebele; Sepedi; SeSotho; SiSwati;Tshivenda;Xitsonga

4. The Transient and Tourist Hotel Questionnaire (English) is divided into the following sections:

5. Name, Age, Gender, Date of Birth, Marital Status, Population Group, Country of birth, Citizenship, Province.

6. The Questionnaire for Institutions (English) is divided into the following sections:

7. Particulars of the institution

8. Availability of piped water for the institution

9. Main source of water for domestic use

10. Main type of toilet facility

11. Type of energy/fuel used for cooking, heating and lighting at the institution

12. Disposal of refuse or rubbish

13. Asset ownership (TV, Radio, Landline telephone, Refrigerator, Internet facilities)

14. List of persons in the institution on census night (name, date of birth, sex, population group, marital status, barcode number)

15. The Post Enumeration Survey Questionnaire (English)

These questionnaires are provided as external resources.

Cleaning operations

Data editing and validation system The execution of each phase of Census operations introduces some form of errors in Census data. Despite quality assurance methodologies embedded in all the phases; data collection, data capturing (both manual and automated), coding, and editing, a number of errors creep in and distort the collected information. To promote consistency and improve on data quality, editing is a paramount phase in identifying and minimising errors such as invalid values, inconsistent entries or unknown/missing values. The editing process for Census 2011 was based on defined rules (specifications).

The editing of Census 2011 data involved a number of sequential processes: selection of members of the editing team, review of Census 2001 and 2007 Community Survey editing specifications, development of editing specifications for the Census 2011 pre-tests (2009 pilot and 2010 Dress Rehearsal), development of firewall editing specifications and finalisation of specifications for the main Census.

Editing team The Census 2011 editing team was drawn from various divisions of the organisation based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors. Census 2011 editing team was drawn from various divisions of the organization based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors.

The Census 2011 questionnaire was very complex, characterised by many sections, interlinked questions and skipping instructions. Editing of such complex, interlinked data items required application of a combination of editing techniques. Errors relating to structure were resolved using structural query language (SQL) in Oracle dataset. CSPro software was used to resolve content related errors. The strategy used for Census 2011 data editing was implementation of automated error detection and correction with minimal changes. Combinations of logical and dynamic imputation/editing were used. Logical imputations were preferred, and in many cases substantial effort was undertaken to deduce a consistent value based on the rest of the household’s information. To profile the extent of changes in the dataset and assess the effects of imputation, a set of imputation flags are included in the edited dataset. Imputation flags values include the following: 0 no imputation was performed; raw data were preserved 1 Logical editing was performed, raw data were blank 2 logical editing was performed, raw data were not blank 3 hot-deck imputation was performed, raw data were blank 4 hot-deck imputation was performed, raw data were not blank

Data appraisal

Independent monitoring and evaluation of Census field activities Independent monitoring of the Census 2011 field activities was carried out by a team of 31 professionals and 381 Monitoring

Please Note: Community Reporting Areas (CRA) have been updated to follow the 2020 census tract lines which resulted in minor changes to some boundary conditions. They have also been extended into water areas to allow the assignment of CRAs to overwater housing and businesses. To exclude the water polygons from a map choose the filter, water=0.Community reporting areas (CRAs) are designed to address a gap that existed in city geography. The task of reporting citywide information at a "community-like level" across all departments was either not undertaken or it was handled in inconsistent ways across departments. The CRA geography provides a "common language" for geographic description of the city for reporting purposes. Therefore, this geography may be used by departments for geographic reporting and tracking purposes, as appropriate. The U.S. Census Bureau census tract geography was chosen as the basis of the CRA geography due to their stability through time and link to widely-used demographic data.The following criteria for a CRA geography were defined for this effort:no overlapping areascomplete coverage of the citysuitable scale to represent neighborhood areas/conditionsreasonably stable over timeconsistent with census geographyrelatively easy to use in a data contextfamiliar system of common place namesrespects neighborhood district geography to the extent possibleThe following existing geographies were reviewed during this effort:neighborhood planning areas (DON)neighborhood districts (DON/CNC/Neighborhood District Councils)city sectors/neighborhood plan implementation areas (DON)urban centers/urban villages (DPD)population sub-areas (DPD)Neighborhood Map Atlas (City Clerk)Census tract geographytopographyvarious other geographic information sources related to neighborhood areas and common place namesThis is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

Analysis of ‘Community Reporting Areas’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/73623efd-3088-49c7-b51b-cdbc119b2af8 on 12 February 2022.

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

Community reporting areas (CRAs) are designed to address a gap that existed in city geography. The task of reporting citywide information at a "community-like level" across all departments was either not undertaken or it was handled in inconsistent ways across departments. The CRA geography provides a "common language" for geographic description of the city for reporting purposes. Therefore, this geography may be used by departments for geographic reporting and tracking purposes, as appropriate. The following criteria for a CRA geography were defined for this effort: -no overlapping areas; -complete coverage of the city; -suitable scale to represent neighborhood areas/conditions; -reasonably stable over time; -consistent with census geography; -relatively easy to use in a data context; -familiar system of common place names; and, -respects neighborhood district geography. The following existing geographies were reviewed during this effort: -neighborhood planning areas (DON); -neighborhood districts (DON/CNC/Neighborhood District Councils); -city sectors/neighborhood plan implementation areas (DON); -urban centers/urban villages (DPD); -population sub-areas (DPD); -Neighborhood Map Atlas (City Clerk); -Census 2000 geography; -topography; and, -various other geographic information sources related to neighborhood areas and common place names. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

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

Community reporting areas (CRAs) are designed to address a gap that existed in city geography. The task of reporting citywide information at a "community-like level" across all departments was either not undertaken or it was handled in inconsistent ways across departments. The CRA geography provides a "common language" for geographic description of the city for reporting purposes. Therefore, this geography may be used by departments for geographic reporting and tracking purposes, as appropriate. The following criteria for a CRA geography were defined for this effort: -no overlapping areas; -complete coverage of the city; -suitable scale to represent neighborhood areas/conditions; -reasonably stable over time; -consistent with census geography; -relatively easy to use in a data context; -familiar system of common place names; and, -respects neighborhood district geography. The following existing geographies were reviewed during this effort: -neighborhood planning areas (DON); -neighborhood districts (DON/CNC/Neighborhood District Councils); -city sectors/neighborhood plan implementation areas (DON); -urban centers/urban villages (DPD); -population sub-areas (DPD); -Neighborhood Map Atlas (City Clerk); -Census 2000 geography; -topography; and, -various other geographic information sources related to neighborhood areas and common place names. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.

Wisconsin municipal ward data collected in January 2025 by LTSB. [Attribute Definitions]. This data has been collected in regards to state statute 15(4)(br)1. County clerks will transmit municipal, municipal ward, and county supervisory districts in GIS format to LTSB by January 15th and July 15th* per statute 5.15(4)(br)1: "...no later than January 15 and July 15 of each year*, the county clerk shall transmit to the Legislative Technology Services Bureau a report confirming the boundaries of each municipality, ward, and supervisory district in the county together with a map of the county, in an electronic format approved by the Legislative Technology Services Bureau. Each report shall be current to the nearest January 1 or July 1* preceding the date of the report”. (*with the exception of years ending in “01” where data collection will align closer to typical redistricting timelines of March and October 15)Municipal clerks need to notify the county clerk within 5 days of any boundary change per statute 5.15(4)(b): "Within 5 days after adoption or enactment of an ordinance or resolution under this section or any amendment thereto, the municipal clerk shall transmit one copy of the ordinance or resolution or the amendment to the county clerk of each county in which the municipality is contained, accompanied by the list and map specified in par. (a). Each copy shall identify the name of the municipality and the county or counties in which it is located."Municipal data collected in the January collections will be used by LTSB to update municipal boundaries the U.S. Census Bureau’s TIGER database via the Boundary Annexation Survey (BAS). Counties and municipalities are no longer required to submit boundary changes directly to the Census Bureau. LTSB will submit data to the Census Bureau for the state as a whole.Section 13.96(1)(b) of the Wisconsin Statutes requires LTSB to “upon receipt of municipal boundary information at each reporting interval, reconcile and compile the information received to produce a statewide data base consisting of municipal boundary information for the entire state”.Section 13.96(1)(c) states that LTSB shall “Participate, on behalf of this state, in geographic boundary information programs when offered by the U.S. bureau of the census”.LTSB will publish Municipal Wards, Municipal Boundaries (cities, towns, villages), and County Supervisory Districts to the LTSB GIS HUB website.This data has been collected with the LTSB GeoData Collector.*with the exception of years ending in “01” where data collection will align closer to typical redistricting timelines of March and October 15.

The boundary of the individual Board Districts was provided by the Rancho Simi Rec and Park District to the Ventura County Clerk/Recorder Elections Division. These boundaries are based on Census data from the 2020 census. The census data does not follow current GIS data for the County of Ventura. The data was used to modify the Election Precincts as maintained by the Ventura County Clerk/Recorder Elections Division. The boundary was then provided to Information Technology Services Department/GIS division to be matched up to the boundary of the School District. The interior lines were redrawn to match Election Precinct polygons. The next scheduled changes should be for the 2030 census data in 2032. The Political boundaries extends 3 miles offshore but the polygons only reflect the land area.