PROBLEM AND OPPORTUNITY In the United States, voting is largely a private matter. A registered voter is given a randomized ballot form or machine to prevent linkage between their voting choices and their identity. This disconnect supports confidence in the election process, but it provides obstacles to an election's analysis. A common solution is to field exit polls, interviewing voters immediately after leaving their polling location. This method is rife with bias, however, and functionally limited in direct demographics data collected. For the 2020 general election, though, most states published their election results for each voting location. These publications were additionally supported by the geographical areas assigned to each location, the voting precincts. As a result, geographic processing can now be applied to project precinct election results onto Census block groups. While precinct have few demographic traits directly, their geographies have characteristics that make them projectable onto U.S. Census geographies. Both state voting precincts and U.S. Census block groups: are exclusive, and do not overlap are adjacent, fully covering their corresponding state and potentially county have roughly the same size in area, population and voter presence Analytically, a projection of local demographics does not allow conclusions about voters themselves. However, the dataset does allow statements related to the geographies that yield voting behavior. One could say, for example, that an area dominated by a particular voting pattern would have mean traits of age, race, income or household structure. The dataset that results from this programming provides voting results allocated by Census block groups. The block group identifier can be joined to Census Decennial and American Community Survey demographic estimates. DATA SOURCES The state election results and geographies have been compiled by Voting and Election Science team on Harvard's dataverse. State voting precincts lie within state and county boundaries. The Census Bureau, on the other hand, publishes its estimates across a variety of geographic definitions including a hierarchy of states, counties, census tracts and block groups. Their definitions can be found here. The geometric shapefiles for each block group are available here. The lowest level of this geography changes often and can obsolesce before the next census survey (Decennial or American Community Survey programs). The second to lowest census level, block groups, have the benefit of both granularity and stability however. The 2020 Decennial survey details US demographics into 217,740 block groups with between a few hundred and a few thousand people. Dataset Structure The dataset's columns include: Column Definition BLOCKGROUP_GEOID 12 digit primary key. Census GEOID of the block group row. This code concatenates: 2 digit state 3 digit county within state 6 digit Census Tract identifier 1 digit Census Block Group identifier within tract STATE State abbreviation, redundent with 2 digit state FIPS code above REP Votes for Republican party candidate for president DEM Votes for Democratic party candidate for president LIB Votes for Libertarian party candidate for president OTH Votes for presidential candidates other than Republican, Democratic or Libertarian AREA square kilometers of area associated with this block group GAP total area of the block group, net of area attributed to voting precincts PRECINCTS Number of voting precincts that intersect this block group ASSUMPTIONS, NOTES AND CONCERNS: Votes are attributed based upon the proportion of the precinct's area that intersects the corresponding block group. Alternative methods are left to the analyst's initiative. 50 states and the District of Columbia are in scope as those U.S. possessions voting in the general election for the U.S. Presidency. Three states did not report their results at the precinct level: South Dakota, Kentucky and West Virginia. A dummy block group is added for each of these states to maintain national totals. These states represent 2.1% of all votes cast. Counties are commonly coded using FIPS codes. However, each election result file may have the county field named differently. Also, three states do not share county definitions - Delaware, Massachusetts, Alaska and the District of Columbia. Block groups may be used to capture geographies that do not have population like bodies of water. As a result, block groups without intersection voting precincts are not uncommon. In the U.S., elections are administered at a state level with the Federal Elections Commission compiling state totals against the Electoral College weights. The states have liberty, though, to define and change their own voting precincts https://en.wikipedia.org/wiki/Electoral_precinct. The Census Bureau practices "data suppression", filtering some block groups from demographic publication because they do not meet a population threshold. This practice...

Electoral registrations for parliamentary and local government elections as recorded in electoral registers for England, Wales, Scotland and Northern Ireland.

Immigration and demographic change have become highly salient in American politics, partly because of the 2016 campaign of Donald Trump. Previous research indicates that local influxes of immigrants or unfamiliar ethnic groups can generate threatened responses, but has either focused on non-electoral outcomes or has analyzed elections in large geographic units such as counties. Here, we examine whether demographic changes at low levels of aggregation were associated with vote shifts toward an anti-immigration presidential candidate between 2012 and 2016. To do so, we compile a novel, precinct-level data set of election results and demographic measures for almost 32,000 precincts in the states of Florida, Georgia, Michigan, Nevada, Ohio, Pennsylvania, and Washington. We employ regression analyses varying model specifications and measures of demographic change. Our estimates uncover little evidence that influxes of Hispanics or non-citizen immigrants benefited Trump relative to past Republicans, instead consistently showing that such changes were associated with shifts to Trump's opponent.

The 2024 results file includes the compilation of the official 2024 UK General Election results, notional 2019 election results, publicly available candidate information, census data, and other contextual information.

Wards for Worcester, MA that reflect Census 2020 data, finalized by the Massachusetts Secretary of the Commonwealth in collaboration with the Worcester City Clerk. These boundaries have been approved by the Local Election District Review Commission (LEDRC) and apply for electoral purposes starting in 2022. The City Councilors elected in the municipal election on November 2, 2021 continued to represent Worcester residents and voters in alignment with the previous 2010 Census-derived boundaries until a new council was elected and sworn in January 2024.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.

Abstract: The Database on Ideology, Money in Politics, and Elections (DIME) is intended as a general resource for the study of campaign finance and ideology in American politics. The database was developed as part of the project on Ideology in the Political Marketplace, which is an on-going effort to perform a comprehensive ideological mapping of political elites, interest groups, and donors using the common-space CFscore scaling methodology (Bonica 2014). Constructing the database required a large-scale effort to compile, clean, and process data on contribution records, candidate characteristics, and election outcomes from various sources. The resulting database contains over 130 million political contributions made by individuals and organizations to local, state, and federal elections spanning a period from 1979 to 2014. A corresponding database of candidates and committees provides additional information on state and federal elections. The DIME+ data repository on congressional activity extends DIME to cover detailed data on legislative voting, lawmaking, and political rhetoric. (See http://dx.doi.org/10.7910/DVN/BO7WOW for details.) The DIME data is available for download as a standalone SQLite database. The SQLite database is stored on disk and can be accessed using a SQLite client or queried directly from R using the RSQLite package. SQLite is particularly well-suited for tasks that require searching through the database for specific individuals or contribution records. (Click here to download.) Overview: The database is intended to make data on campaign finance and elections (1) more centralized and accessible, (2) easier to work with, and (3) more versatile in terms of the types of questions that can be addressed. A list of the main value-added features of the database is below: Data processing: Names, addresses, and occupation and employer titles have been cleaned and standardized. Unique identifiers: Entity resolution techniques were used to assign unique identifiers for all individual and institutional donors included in the database. The contributor IDs make it possible to track giving by individuals across election cycles and levels of government. Geocoding: Each record has been geocoded and placed into congressional districts. The geocoding scheme relies on the contributor IDs to assign a complete set of consistent geo-coordinates to donors that report their full address in some records but not in others. This is accomplished by combining information on self-reported address across records. The geocoding scheme further takes into account donors with multiple addresses. Geocoding was performed using the Data Science Toolkit maintained by Pete Warden and hosted at http://www.datasciencetoolkit.org/. Shape files for congressional districts are from Census.gov (http://www.census.gov/rdo/data). Ideological measures: The common-space CFscores allow for direct distance comparisons of the ideal points of a wide range of political actors from state and federal politics spanning a 35 year period. In total, the database includes ideal point estimates for 70,871 candidates and 12,271 political committees as recipients and 14.7 million individuals and 1.7 million organizations as donors. Corresponding data on candidates, committees, and elections: The recipient database includes information on voting records, fundraising statistics, election outcomes, gender, and other candidate characteristics. All candidates are assigned unique identifiers that make it possible to track candidates if they campaign for different offices. The recipient IDs can also be used to match against the database of contribution records. The database also includes entries for PACs, super PACs, party committees, leadership PACs, 527s, state ballot campaigns, and other committees that engage in fundraising activities. Identifying sets of important political actors: Contribution records have been matched onto other publicly available databases of important political actors. Examples include: Fortune 500 directors and CEOs: (Data) (Paper) Federal court judges: (Data) (Paper} State supreme court justices: (Data) (Paper} Executives appointees to federal agencies: (Data) (Paper) Medical professionals: (Data) (Paper)

• Description: This is the file that was created by entering the data from the appendices per polling station, which were filled in during the central counting of votes for the election of the members of the municipal council of Utrecht. The publication of these files promotes the transparency and verifiability of the process leading to the determination of the result. In addition, people and organizations can take note of the results, carry out analyses, create visualisations, etc. • Source: municipality of Utrecht • Restrictions: the file is published in the interest of openness and transparency regarding elections. No rights of any kind can be derived from the file. • Possibilities: the file is published to enable people and organizations to take note of the results, perform analyses, create visualisations, etc.

This is a do-file, which processes publicly available CCES and Census data available at the URL cited in the references. The second file is correct, it is not clear how to delete the duplicate.

The Record of American Democracy (ROAD) data provide election returns, socioeconomic summaries, and demographic details about the American public at unusually low levels of geographic aggregation. The NSF-supported ROAD project spans every state in the country from 1984 through 1990 (including some off-year elections). These data enable research on topics such as electoral behavior, the political characteristics of local community context, electoral geography, the role of minority groups in elections and legislative redistricting, split ticket voting and divided government, and elections under federalism. Another set of files has added to these roughly 30-40 political variables an additional 3,725 variables merged from the 1990 United States Census for 47,327 aggregate units called MCD Groups. The MCD Group is a construct for purposes of this data collection. It is based on a merging of the electoral precincts and Census Minor Civil Divisions (MCDs). An MCD is about the size of a city or town. An MCD Group is smaller than or equal to a county and (except in California) is greater than or equal to the size of an MCD. The MCD Group units completely tile the United States landmass. This particular study contains the files for the State Level MCD Group Data for the state of Kansas. Documentation and frequently asked questions are available online at the ROAD Website. A downloadable PDF codebook is also available in the files section of this study.

These wards were produced by the Legislative Technology Services Bureau for the 2011 Legislative Redistricting Project. Election data from the current decade is included.Election Data Attribute Field Definitions | Wisconsin Cities, Towns, & Villages Data AttributesWard Data Overview: These municipal wards were created by grouping Census 2010 population collection blocks into municipal wards. This project started with the release of Census 2010 geography and population totals to all 72 Wisconsin counties on March 21, 2011, and were made available via the Legislative Technology Services Bureau (LTSB) GIS website and the WISE-LR web application. The 180 day statutory timeline for local redistricting ended on September 19, 2011. Wisconsin Legislative and Congressional redistricting plans were enacted in 2011 by Wisconsin Act 43 and Act 44. These new districts were created using Census 2010 block geography. Some municipal wards, created before the passing of Act 43 and 44, were required to be split between assembly, senate and congressional district boundaries. 2011 Wisconsin Act 39 allowed communities to divide wards, along census block boundaries, if they were divided by newly enacted boundaries. A number of wards created under Wisconsin Act 39 were named using alpha-numeric labels. An example would be where ward 1 divided by an assembly district would become ward 1A and ward 1B, and in other municipalities the next sequential ward number was used: ward 1 and ward 2. The process of dividing wards under Act 39 ended on April 10, 2012. On April 11, 2012, the United States Eastern District Federal Court ordered Assembly Districts 8 and 9 (both in the City of Milwaukee) be changed to follow the court’s description. On September 19, 2012, LTSB divided the few remaining municipal wards that were split by a 2011 Wisconsin Act 43 or 44 district line.Election Data Overview: Election data that is included in this file was collected by LTSB from the Government Accountability Board (GAB)/Wisconsin Elections Commission (WEC) after each general election. A disaggregation process was performed on this election data based on the municipal ward layer that was available at the time of the election. The ward data that is collected after each decennial census is made up of collections of whole and split census blocks. (Note: Split census blocks occur during local redistricting when municipalities include recently annexed property in their ward submissions to the legislature).Disaggregation of Election Data: Election data is first disaggregated from reporting units to wards, and then to census blocks. Next, the election data is aggregated back up to wards, municipalities, and counties. The disaggregation of election data to census blocks is done based on total population. Detailed Methodology:Data is disaggregated first from reporting unit (i.e. multiple wards) to the ward level proportionate to the population of that ward.The data then is distributed down to the block level, again based on total population.When data is disaggregated to block or ward, we restrain vote totals not to exceed population 18 numbers, unless absolutely required.This methodology results in the following: Election data totals reported to the GAB/WEC at the state, county, municipal and reporting unit level should match the disaggregated election data total at the same levels. Election data totals reported to the GAB at ward level may not match the ward totals in the disaggregated election data file.Some wards may have more election data allocated than voter age population. This will occur if a change to the geography results in more voters than the 2010 historical population limits.Other things of note… We use a static, official ward layer (in this case created in 2011) to disaggregate election data to blocks. Using this ward layer creates some challenges. New wards are created every year due to annexations and incorporations. When these new wards are reported with election data, an issue arises wherein election data is being reported for wards that do not exist in our official ward layer. For example, if "Cityville" has four wards in the official ward layer, the election data may be reported for five wards, including a new ward from an annexation. There are two different scenarios and courses of action to these issues: When a single new ward is present in the election data but there is no ward geometry present in the official ward layer, the votes attributed to this new ward are distributed to all the other wards in the municipality based on population percentage. Distributing based on population percentage means that the proportion of the population of the municipality will receive that same proportion of votes from the new ward. In the example of Cityville explained above, the fifth ward may have five votes reported, but since there is no corresponding fifth ward in the official layer, these five votes will be assigned to each of the other wards in Cityville according the percentage of population.Another case is when a new ward is reported, but its votes are part of reporting unit. In this case, the votes for the new ward are assigned to the other wards in the reporting unit by population percentage; and not to wards in the municipality as a whole. For example, Cityville’s ward five was given as a reporting unit together with wards 1, 4, and 5. In this case, the votes in ward five are assigned to wards one and four according to population percentage. Outline Ward-by-Ward Election Results: The process of collecting election data and disaggregating to municipal wards occurs after a general election, so disaggregation has occurred with different ward layers and different population totals. We have outlined (to the best of our knowledge) what layer and population totals were used to produce these ward-by-ward election results.Election data disaggregates from GAB/WEC Reporting Unit -> Ward [Variant year outlined below]Elections 1990 – 2000: Wards 1991 (Census 1990 totals used for disaggregation)Elections 2002 – 2010: Wards 2001 (Census 2000 totals used for disaggregation)Elections 2012: Wards 2011 (Census 2010 totals used for disaggregation)Elections 2014 – 2016: Wards spring 2017 (Census 2010 totals used for disaggregation)Blocks 2011 -> Centroid geometry and spatially joined with Wards [All Versions]Each Block has an assignment to each of the ward versions outlined aboveIn the event that a ward exists now in which no block exists (Occurred with spring 2017) due to annexations, a block centroid was created with a population 0, and encoded with the proper Census IDs.Wards [All Versions] disaggregate -> Blocks 2011This yields a block centroid layer that contains all elections from 1990 to 2016Blocks 2011 [with all election data] -> Wards 2011 (then MCD 2011, and County 2011) All election data (including later elections such as 2016) is aggregated to the Wards 2011 assignment of the blocksNotes:Population of municipal wards 1991, 2001 and 2011 used for disaggregation were determined by their respective Census.Population and Election data will be contained within a county boundary. This means that even though municipal and ward boundaries vary greatly between versions of the wards, county boundaries have stayed the same. Therefore, data totals within a county should be the same between 2011 wards and 2018 wards.Election data may be different for the same legislative district, for the same election, due to changes in the wards from 2011 and 2018. This is due to (a) boundary corrections in the data from 2011 to 2018, and (b) annexations, where a block may have been reassigned.

City Council Districts for Worcester, MA that reflect Census 2020 data, finalized by the Massachusetts Secretary of the Commonwealth in collaboration with the Worcester City Clerk. These boundaries have been approved by the Local Election District Review Commission (LEDRC) and apply for electoral purposes starting in 2022. Note that the City Councilors elected in the municipal election on November 2, 2021 continued to represent Worcester residents and voters in alignment with the previous 2010 Census-derived boundaries until a new council was elected and sworn in January 2024.Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.

• Description: On Friday, March 24, 2023, the meeting of the Central Electoral Committee of the Province of Utrecht was held. In this session, the number of votes per candidate and per party was determined. The numbers of all municipalities in the Province of Utrecht have been combined in the supporting software elections (osv). The census file comes from this software. You can use the file to check the results. You can also use the file to perform your own analyzes or create visualizations. • Source: Central Elections Office of the Province of Utrecht • Restrictions: We publish the census file to make the elections open and transparent. You cannot derive any rights from the file. • Options: You can use this file to view the results, perform analyses, create visualizations, etc.

Finalized by the office of the Massachusetts Secretary of the Commonwealth in collaboration with Worcester City Clerk. For electoral purposes, this dataset has been superseded by the Voting Precincts Based on 2020 Census Data dataset which applies starting in 2022. The City Councilors elected in the municipal election on November 2, 2021, continued to represent Worcester residents and voters in alignment with these 2010 census-derived boundaries until a new council was elected and sworn in January 2024. Informing Worcester is the City of Worcester's open data portal where interested parties can obtain public information at no cost.

Election Data Attribute Field Definitions | Wisconsin Cities, Towns, & Villages Data Attributes Ward Data Overview:July 2020 municipal wards were collected by LTSB through the WISE-Decade system. Current statutes require each county clerk, or board of election commissioners, no later than January 15 and July 15 of each year, to transmit to the LTSB, in an electronic format (approved by LTSB), a report confirming the boundaries of each municipality, ward and supervisory district within the county as of the preceding “snapshot” date of January 1 or July 1 respectively. Population totals for 2011 wards are carried over to the 2020 dataset for existing wards. New wards created since 2011 due to annexations, detachments, and incorporation are allocated population from Census 2010 collection blocks. LTSB has topologically integrated the data, but there may still be errors.Election Data Overview:The 2012-2020 Wisconsin election data that is included in this file was collected by LTSB from the *Wisconsin Elections Commission (WEC) after each general election. A disaggregation process was performed on this election data based on the municipal ward layer that was available at the time of the election. Disaggregation of Election Data:Election data is first disaggregated from reporting units to wards, and then to census blocks. Next, the election data is aggregated back up to wards, municipalities, and counties. The disaggregation of election data to census blocks is done based on total population. Detailed Methodology:Data is disaggregated first from reporting unit (i.e. multiple wards) to the ward level proportionate to the population of that ward. The data then is distributed down to the block level, again based on total population. When data is disaggregated to block or ward, we restrain vote totals not to exceed population 18 numbers, unless absolutely required.This methodology results in the following: Election data totals reported to the WEC at the state, county, municipal and reporting unit level should match the disaggregated election data total at the same levels. Election data totals reported to the WEC at ward level may not match the ward totals in the disaggregated election data file. Some wards may have more election data allocated than voter age population. This will occur if a change to the geography results in more voters than the 2010 historical population limits.Other things of note…We use a static, official ward layer (in this case created in 2020) to disaggregate election data to blocks. Using this ward layer creates some challenges. New wards are created every year due to annexations and incorporations. When these new wards are reported with election data, an issue arises wherein election data is being reported for wards that do not exist in our official ward layer. For example, if Cityville has four wards in the official ward layer, the election data may be reported for five wards, including a new ward from an annexation. There are two different scenarios and courses of action to these issues: When a single new ward is present in the election data but there is no ward geometry present in the official ward layer, the votes attributed to this new ward are distributed to all the other wards in the municipality based on population percentage. Distributing based on population percentage means that the proportion of the population of the municipality will receive that same proportion of votes from the new ward. In the example of Cityville explained above, the fifth ward may have five votes reported, but since there is no corresponding fifth ward in the official layer, these five votes will be assigned to each of the other wards in Cityville according the percentage of population.Another case is when a new ward is reported, but its votes are part of reporting unit. In this case, the votes for the new ward are assigned to the other wards in the reporting unit by population percentage; and not to wards in the municipality as a whole. For example, Cityville’s ward 5 was given as a reporting unit together with wards 1, 4, and 5. In this case, the votes in ward five are assigned to wards 1 and 4 according to population percentage. Outline Ward-by-Ward Election ResultsThe process of collecting election data and disaggregating to municipal wards occurs after a general election, so disaggregation has occurred with different ward layers and different population totals. We have outlined (to the best of our knowledge) what layer and population totals were used to produce these ward-by-ward election results.Election data disaggregates from WEC Reporting Unit -> Ward [Variant year outlined below]Elections 1990 – 2000: Wards 1991 (Census 1990 totals used for disaggregation)Elections 2002 – 2010: Wards 2001 (Census 2000 totals used for disaggregation)Elections 2012: Wards 2011 (Census 2010 totals used for disaggregation)Elections 2014 – 2016: Wards 2018 (Census 2010 totals used for disaggregation)Elections 2018: Wards 2018Elections 2020: Wards 2020Blocks 2011 -> Centroid geometry and spatially joined with Wards [All Versions]Each Block has an assignment to each of the ward versions outlined aboveIn the event that a ward exists now in which no block exists (occurred with spring 2020) due to annexations, a block centroid was created with a population 0, and encoded with the proper Census IDs.Wards [All Versions] disaggregate -> Blocks 2011This yields a block centroid layer that contains all elections from 1990 to 2018Blocks 2011 [with all election data] -> Wards 2020 (then MCD 2020, and County 2020) All election data (including later elections) is aggregated to the Wards 2020 assignment of the blocksNotes:Population of municipal wards 1991, 2001 and 2011 used for disaggregation were determined by their respective Census.Population and Election data will be contained within a county boundary. This means that even though MCD and ward boundaries vary greatly between versions of the wards, county boundaries have stayed the same, so data should total within a county the same between wards 2011 and wards 2020.Election data may be different for the same legislative district, for the same election, due to changes in the wards from 2011 and 2020. This is due to boundary corrections in the data from 2011 to 2020, and annexations, where a block may have been reassigned.*WEC replaced the previous Government Accountability Board (GAB) in 2016, which replaced the previous State Elections Board in 2008.

description: Ward precincts, which function as local election districts to determine the polling places for voters, based on their addresses. Precincts are based on U.S. Census Bureau blocks. These precincts were first used for the 2012 elections and first used for Chicago municipal elections in 2015.; abstract: Ward precincts, which function as local election districts to determine the polling places for voters, based on their addresses. Precincts are based on U.S. Census Bureau blocks. These precincts were first used for the 2012 elections and first used for Chicago municipal elections in 2015.

The following is excerpted from an online document produced by the U.S. Census Bureau pertaining to voting districts (found at http://www.census.gov/geo/www/cob/vt_metadata.html): "Voting district (VTD) is the generic name for geographic entities, such as precincts, wards, and election districts, established by state, local, and tribal governments for the purpose of conducting elections. States participating in the Census 2000 Redistricting Data Program as part of Public Law 94-171 (1975) may provide boundaries, codes, and names for their VTDs to the U.S. Census Bureau. The U.S. Census Bureau first reported data for VTDs following the 1980 census. Because the U.S. Census Bureau requires that VTDs follow boundaries of census blocks, participating states often adjusted the boundaries of the VTDs they submit for data tabulation purposes to conform to census block boundaries. If requested by the participating state, the U.S. Census Bureau identifies these "adjusted" VTDs as "pseudo-VTDs." For Census 2000, each VTD is identified by a one- to six-character alphanumeric census code that is unique within county. The code "ZZZZZZ" identifies parts of a county in which no VTDs were identified."

As of July 2025, the political party that 18 to 24 year-old's in Great Britain would be most likely to vote for was the Labour Party, at 33 percent, with Labour also the most popular party among those aged 25 to 49. Reform UK was the most popular party for the 50 to 64 age group, with 29 percent of voters saying they would vote for them. For the oldest age group, the Reform was also the most popular, with 35 percent of over 65s intending to vote for them. Reform surge in the polls Since winning the last UK general election in July 2024, the ruling Labour Party have steadily become more unpopular among voters. After winning 33.7 percent of the vote in that election, the party was polling at 24 percent in April 2025, only slightly ahead of Reform UK on 23 percent. A right-wing populist party, Reform benefited from the collapse in support for the center-right Conservative Party in the last election, winning several seats at their expense. While the next UK general election is not due to be held until 2029, the government will be keen to address their collapsing approval ratings, in the face of Reform's rising support. Economic headaches for Labour in 2025 Although Labour inherited a growing economy, with falling inflation, and low unemployment from the Conservatives, the overall economic outlook for the UK is still quite gloomy. The country's government debt is around 100 percent of GDP, and without large tax rises and spending cuts, the government hopes to create a stronger, more resilient economy to reduce the deficit. While this is still a possibility, the UK's economic prospects for 2025 were recently slashed, with growth of one percent forecast, down from an earlier prediction of two percent. Although mainly due to external factors such as the threat of increasing tariffs, and general geopolitical instability, the UK's faltering economy will add further problems to the embattled government.

Population aged 15 years and over by sex and highest level of education completed by Local Electoral Areas. (Census 2022 Theme 10 Table 4 )Census 2022 table 10.4 is population aged 15+ by highest level of education completed. Attributes include a breakdown of population by highest level of education completed and sex. Census 2022 theme 10 is Education. For the purposes of Local Authority elections, each county and city is divided into Local Electoral Areas (LEAs) which are constituted on the basis of Orders made under the Local Government Act, 1941. Statutory Instruments 610-638 of 2018 and 6-8, 27-28, 156-157 of 2019 state the current composition of LEAs.In general, LEAs are formed by aggregating Electoral Divisions. However, in a number of cases, Electoral Divisions are split between LEAs and in order to render them suitable for the production of statistics, the CSO has amended some LEA boundaries to ensure that statistical disclosure does not occur. As a result of these amendments, Census 2022 LEAs are comprised of whole Census 2022 Electoral Divisions.Coordinate reference system: Irish Transverse Mercator (EPSG 2157). These boundaries are based on 20m generalised boundaries sourced from Tailte Éireann Open Data Portal. CSO Local Electoral Areas 2022

The following is excerpted from an online document produced by the U.S. Census Bureau pertaining to voting districts (found at http://www.census.gov/geo/www/cob/vt_metadata.html):"Voting district (VTD) is the generic name for geographic entities, such as precincts, wards, and election districts, established by state, local, and tribal governments for the purpose of conducting elections. States participating in the Census 2000 Redistricting Data Program as part of Public Law 94-171 (1975) may provide boundaries, codes, and names for their VTDs to the U.S. Census Bureau. The U.S. Census Bureau first reported data for VTDs following the 1980 census. Because the U.S. Census Bureau requires that VTDs follow boundaries of census blocks, participating states often adjusted the boundaries of the VTDs they submit for data tabulation purposes to conform to census block boundaries. If requested by the participating state, the U.S. Census Bureau identifies these "adjusted" VTDs as "pseudo-VTDs."For Census 2000, each VTD is identified by a one- to six-character alphanumeric census code that is unique within county. The code "ZZZZZZ" identifies parts of a county in which no VTDs were identified."

This GIS layer contains the geographical boundaries of the 2020 census blocks for Loudoun County, Virginia. The 2020 Census block boundaries were used for statistical data collection and tabulation purposes for the 2020 Decennial Census. Census blocks are the smallest geographic area for publishing data from the decennial Census. The geographical area covered by this geographic feature class is generally very small in densely settled areas, for instance one city block. In sparsely settled areas they may cover several square miles. Census blocks nest within every 2020 Census geographic area (i.e. block groups, tracts, census designated places, and local, state, and federal election districts). This nesting of blocks allows Census Bureau statistical data to be tabulated to the appropriate geographic areas by aggregating the block data up. Census blocks are uniquely numbered within census tracts, with the blocks valid range being 1 to 9999 with leading zeros added (i.e. 0001, 0023) when necessary to create a four digit unique identifier. This 2010 Census block layer is based on the U.S. Census Bureau Census 2020 TIGER/Line files. The boundaries are an extract of aerial photography and cartographic information, such as roads and streams, from the Loudoun County GIS system. Census Blocks are bounded on all sides by visible features, such as roads, streams, lakes, power lines, and railroad tracks, and/or by non-visible boundaries such as town and county boundaries, and short line-of-sight extensions of streets and roads.