Every four years in the United States, the electoral college system is used to determine the winner of the presidential election. In this system, each state has a fixed number of electors based on their population size, and (generally speaking) these electors then vote for their candidate with the most popular votes within their state or district. Since 1964, there have been 538 electoral votes available for presidential candidates, who need a minimum of 270 votes to win the election. Because of this system, candidates do not have to win over fifty percent of the popular votes across the country, but just win in enough states to receive a total of 270 electoral college votes. Popular results From 1789 until 1820, there was no popular vote, and the President was then chosen only by the electors from each state. George Washington was unanimously voted for by the electorate, receiving one hundred percent of the votes in both elections. From 1824, a popular vote has been conducted among American citizens (with varying levels of access for women, Blacks, and poor voters), to help electors in each state decide who to vote for (although the 1824 winner was chosen by the House of Representatives, as no candidate received over fifty percent of electoral votes). Since 1924, the difference in the share of both votes has varied, with several candidates receiving over 90 percent of the electoral votes while only receiving between fifty and sixty percent of the popular vote. The highest difference was for Ronald Reagan in 1980, where he received just 50.4 percent of the popular vote, but 90.9 percent of the electoral votes. Unpopular winners Since 1824, there have been 51 elections, and in 19 of these the winner did not receive over fifty percent of the popular vote. In the majority of these cases, the winner did receive a plurality of the votes, however there have been five instances where the winner of the electoral college vote lost the popular vote to another candidate. The most recent examples of this were in 2000, when George W. Bush received roughly half a million fewer votes than Al Gore, and in 2016, where Hillary Clinton won approximately three million more votes than Donald Trump.

NYU Libraries has licensed access to the L2 Political Academic Voter File. The file is a continuously updated dataset consisting of public information for every registered voter in the United States and includes basic socio-demographic indicators (some of which are modeled), consumer preferences, political party affiliation, voting history, and more.

The data consists of .tab files organized into individual state folders (all states and DC). Each state folder contains two files: demographics data and voter history data, with a data dictionary for each dataset. The size of the folders vary by state and data for all states adds up to approximately 40 GB. The data is organized into releases, generally two per year (spring and fall), which represent a snapshot of the country's voters at the time of the dataset creation.

NYU has also licensed access to L2 Political historical backlog of data. This backlog includes versions of the L2 Processed voter file going back to 2008 (for most U.S. states) and unprocessed "raw" state voter rolls, also going back to 2008 for most U.S. states.

This collection is available to NYU faculty and students only, and requires user to first submit a data management plan to account for how access and storage of the data will be handled. Information on how to submit a request to use this data and create a data management plan is available at https://guides.nyu.edu/l2political.

These data are derived from CANDIDATE NAME AND CONSTITUENCY TOTALS, 1788-1990 (ICPSR 0002). They consist of returns for two-thirds of all elections from 1788 to 1823 to the offices of president, governor, and United States representative, and over 90 percent of all elections to those offices since 1824. They also include information on United States Senate elections since 1912. Returns for one additional statewide office are included beginning with the 1968 election. This file provides a set of derived measures describing the vote totals for candidates and the pattern of contest in each constituency. These measures include the total number of votes cast for all candidates in the election, each candidate's percentage of the vote received, and several measures of the relative performance of each candidate. They are appended to the individual candidate records and permit extensive analysis of electoral contests over time. This dataset contains returns for all parties and candidates (as well as scattering vote) for general elections and special elections, including information on elections for which returns were available only at the constituency level. Included in this edition are data from the District of Columbia election for United States senator and United States representative. The offices of two senators and one representative were created by the "District of Columbia Statehood Constitutional Convention Initiative," which was approved by District voters in 1980. Elections for these offices were postponed until the 1990 general election. The three offices are currently local District positions, which will turn into federal offices if the District becomes a state.

Throughout United States history, voter turnout among the voting eligible population has varied, ranging from below twelve percent in uncontested elections, to 83 percent in the 1876 election. In early years, turnout in presidential elections was relatively low, as the popular vote was not used in every state to decide who electors would vote for. When this was changed in the 1824 election, turnout increased dramatically, and generally fluctuated between seventy and eighty percent during the second half of the nineteenth century. Until the 1840 and 1842 elections, midterm elections also had a higher turnout rate than their corresponding presidential elections, although this trend has been reversed since these years.

Declining turnout in the twentieth century An increase in voting rights, particularly for black males in 1870 and for women in 1920, has meant that the share of the total population who are legally eligible to vote has increased significantly; yet, as the number of people eligible to vote increased, the turnout rate generally decreased. Following enfranchisement, it would take over fifty years before the female voter turnout would reach the same level as males, and over 150 years before black voters would have a similar turnout rate to whites. A large part of this was simply the lack of a voting tradition among these voter bases; however, the Supreme Court and lawmakers across several states (especially in the south) created obstacles for black voters and actively enforced policies and practices that disenfranchised black voter participation. These practices were in place from the end of the Reconstruction era (1876) until the the Voting Rights Act of 1965 legally removed and prohibited many of these obstacles; nonetheless, people of color continue to be disproportionally affected by voting restrictions to this day.

Recent decades In 1971, the Twenty-sixth Amendment lowered the minimum voting age in most states from 21 to 18 years old, which greatly contributed to the six and eight percent reductions in voter turnout in the 1972 and 1974 elections respectively, highlighting a distinct correlation between age and voter participation. Overall turnout remained below sixty percent from the 1970s until the 2004 election, and around forty percent in the corresponding midterms. In recent elections, increased political involvement among younger voters and those from ethnic minority backgrounds has seen these numbers rise, with turnout in the 2018 midterms reaching fifty percent. This was the highest midterm turnout in over one hundred years, leading many at the time to predict that the 2020 election would see one of the largest and most diverse voter turnouts in the past century, although these predictions then reversed with the arival of the coronavirus (COVID-19) pandemic. However, 2020 did prove to have the highest turnout in any presidential election since 1900; largely as a result of mail-in voting, improved access to early voting, and increased activism among grassroots organizations promoting voter registration.

This special topic poll, conducted October 19-22, 2006, is part of a continuing series of monthly surveys that solicit public opinion on the current presidency and on a range of other political and social issues. Respondents were asked whether they approved of the way George W. Bush was handling his job as president, whether they approved of the way Congress and their own representative in Congress was handling their job, and to rate the condition of the national economy. Registered voters were asked whether they followed the congressional elections, whether they were likely to vote, and which candidate they would vote for if the election were being held that day. Registered voters who had already voted absentee were asked which candidate they voted for, how enthusiastic they were about their vote, and whether their vote was more for one political party, or more against the other political party. Opinions were solicited on what was the most important issue in congressional elections, whether things in the country were generally going in the right direction, whether their reason for voting for a candidate for Congress included showing support for George W. Bush, which political party they trusted to do a better job handling issues such as the situation in Iraq and the economy, and whether they thought a change of control from the Republicans to the Democrats would be a good thing. Information was collected on whether respondents had been contacted by any organization working in support of a candidate for Congress and which political party they were asked to vote for, whether the 2006 congressional elections were more important to the country than past elections, and whether the war with Iraq was worth fighting. Additional questions asked how much Congress should be blamed for problems relating to the war with Iraq, how much credit Congress should get for preventing terrorist attacks, whether respondents felt optimistic about the situation in Iraq, and if the United States had the same kind of involvement in the war with Iraq as it did the Vietnam war. Demographic variables include sex, age, religion, race, education level, household income, labor union membership, voter registration and participation history, political party affiliation, political philosophy, employment status, marital status, and type of residential area (e.g., urban or rural).

Researchers studying electoral participation often rely on post-election surveys. However, the reported turnout rate is usually much higher in survey samples than in reality. Survey methodology research has shown that offering abstainers the opportunity to use face-saving response options succeeds at reducing overreporting by a range of 4 to 8 percentage points. This finding rests on survey experiments conducted in the United States after national elections. We offer a test of the efficacy of the face-saving response items through a series of wording experiments embedded in 19 post-election surveys in Europe and Canada, at four different levels of government. With greater variation in contexts, our analyses reveal a distribution of effect sizes ranging from null to minus 18 percentage points.

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).

State, county, and New England town-level data of votes in United States Senate elections. Includes candidate names and parties. Cumulative state-level vote totals have been compiled by CCSS staff.

Dave Leip's website

The Dave Leip website here: https://uselectionatlas.org/BOTTOM/store_data.php has additional years of data available going back to 1990 but at a fee. Sometimes the files are updated by Dave Leip, and new versions are made available, but CCSS is not notified. If you suspect the file you want may be updated, please get in touch with CCSS Data Services. These files were last checked for updates on 19 February 2024.

Note that file version numbers are those assigned to them by Dave Leip's Election Atlas. Please refer to the CCSS Data and Reproduction Archive Version number in your citations for the full dataset.

For additional information on file layout, etc. see: https://uselectionatlas.org/BOTTOM/DOWNLOAD/spread_national.html

Similar publically available state-level data dating back to 1976 is available at https://doi.org/10.7910/DVN/PEJ5QU

Precinct-level publically available data for 2016 is available at https://doi.org/10.7910/DVN/NLTQAD

August 18, 2020, marked one hundred years since the ratification of the 19th Amendment to the U.S. Constitution, which declared that neither individual states nor the federal government could prohibit people from voting on the basis of their gender. Prior to the amendment's passing in the Senate, almost half the states had already lifted all (or most) of the gender-related restrictions that applied to the voting process. When Tennessee ratified the amendment, it became the 36th state to do so, which meant that the amendment came into effect nationwide. It is important to note that, while the 19th Amendment legally granted all eligible women the right to vote, the reality in many states was that most women belonging to ethnic minorities, or those living in poverty, continued to be disenfranchised by oppressive laws; such as citizenship and Jim Crow laws. Pre-19th Amendment In the colonial and early-independence era, restrictions preventing women from voting were often unclear and varied from state to state. Towards the turn of the nineteenth century, however, most states had already put firm restrictions in place, so that only white, Protestant, property-holding males could vote. The religious and property restrictions were mostly repealed by the mid-1800s, and the first state to grant women suffrage was Wyoming in 1869 (while it was still a territory). The issue of suffrage came to the forefront of the women's civil rights movement in the 1850s, and by the end of the century, a series of high-profile protests and lawsuits had garnered nationwide support. A number of states, particularly in the west, gradually began to introduce female suffrage by the 1910s, before the 19th Amendment was eventually passed in the Senate in 1919. 22 states ratified the amendment by the year's end, and Tennessee became the 36th state to do so on August 18, 1920. This approval meant that the law had been ratified in two thirds of U.S. states (eight states voted against it), and therefore it took effect on a nationwide level on this day. Post-19th Amendment After the amendment came into effect nationwide, ratifying the bill on a state level became an inconsequential formality; nonetheless, it would take a number of states several decades to formally pass the bill, with Mississippi becoming the last to do so in 1984. The only two states who did not ratify the amendment were Alaska and Hawaii, who were admitted to the union after the bill's passing. Most Native Americans were granted citizenship in 1924, and the oppressive laws and practices that restricted ethnic minorities (such as poll taxes and literacy tests) were legally repealed and prohibited in the 1960s or 1970s. In the past century, female voter participation has gradually increased, and it has exceeded male turnout in all presidential elections since 1980. Recent general elections have seen a surge in the number of women running for office and the 2018 midterms saw a record number of women elected to Congress.

This dataset represents the results of the 4-digit match performed using the Social Security - Help America Vote Verification (HAVV) system.

This dataset represents the results of the 4-digit match performed using the Social Security - Help America Vote Verification (HAVV) system. Report for week ending August 19, 2023.

CodeThis figshare repository hosts a collection of tools and scripts for Twitter data analysis, focusing on Election Prediction using sentiment analysis and tweet processing. The repository includes four key files:twitter_data_collection.py: This Python script is designed for collecting tweets from Twitter in JSON format. It provides a robust method for gathering data from the Twitter platform.EP.ipynb: EP.ipynb" is designed for sentiment analysis and tweet processing. It features three sentiment analysis methods: VADER, BERT, and BERTweet. It includes a US states dictionary for geolocating and categorizing tweets by state, providing sentiment analysis results in both volumetric and percentage formats. Furthermore, it offers time-series analysis options, particularly on a monthly basis. It also includes a feature for filtering COVID-19-related tweets. Additionally, it conducts election analysis at both state and country levels, giving insights into public sentiment and engagement regarding political elections.Datasetbiden and trump.csv Files:The "biden.csv" and "trump.csv" files together constitute an extensive dataset of tweets related to two prominent U.S. political figures, Joe Biden and Donald Trump. These files contain detailed information about each tweet, including the following key attributes:create_date: The date the tweet was created.id: A unique identifier for each tweet.tweet_text: The actual text content of the tweet.user_id: The unique identifier for the Twitter user who posted the tweet.user_name: The name of the Twitter user.user_screen_name: The Twitter handle of the user.user_location: The location provided by the user in their Twitter profile.state (location): The U.S. state associated with the user's provided location.text_clean: The tweet text after preprocessing, making it suitable for analysis.Additionally, sentiment analysis has been applied to these tweets using two different methods:VADER Sentiment Analysis: Each tweet has been assigned a sentiment score and a sentiment category (positive, negative, or neutral) using VADER sentiment analysis. The sentiment scores are provided in the "Vader_score" column, and the sentiment categories are in the "Vader_sentiment" column.BERTweet Sentiment Analysis: The files also feature sentiment labels assigned using the BERTweet sentiment analysis method, along with associated sentiment scores. The sentiment labels can be found in the "Sentiment" column, and the cleaned sentiment labels are available in the "Sentiment_clean" column.This combined dataset offers a valuable resource for exploring sentiment trends, conducting research on public sentiment, and analyzing Twitter users' opinions related to Joe Biden and Donald Trump. Researchers, data analysts, and sentiment analysis practitioners can utilize this data for a wide range of studies and projects.This repository serves as a resource for collecting, processing, and analyzing Twitter data with a focus on sentiment analysis. It offers a range of tools and datasets to support research and experimentation in this area.

This election poll, fielded November 26, 2000, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. This data collection focused on the presidential election that took place on November 7, 2000. The poll queried respondents about the situation in the country 19 days after the election. Respondents were asked about the extent of their personal interest in the post-election situation in the country, whom they wanted to see become the next president, the legitimacy of this election, and their confidence about the accuracy of Florida's recount. They also expressed their views about whether, after the Secretary of State in Florida had declared George W. Bush the winner, Al Gore should concede or if he should ask the courts to review the vote. Questions elicited respondents' opinions about whether the United States Supreme Court and the Florida state legislature should be involved in determining the winner of the election in Florida and whether ballots with dimpled or indented chads should be counted as votes. Respondents answered additional questions on whether the Secretary of State in Florida did the right thing in denying Palm Beach County officials' request to extend the deadline for a hand recount, and whether respondents wanted to end the unclear situation quickly or give both campaigns a chance to make their full case in court. Background information on respondents includes age, gender, education, race, party affiliation, political orientation, and voter registration.

The 18th presidential election of the United States was contested in 1856 by James Buchanan of the Democratic Party, John C Frémont of the Republican Party, and former President Millard Fillmore of the Native American (Know Nothing) Party. This was the first time that the Republican Party (founded in 1854) fielded a nominee, and, although unsuccessful here, the Republicans would go on to win 13 of the next 15 US presidential elections. Results No candidate won over half of the popular vote, however Buchanan's plurality did give him 59 percent of the electoral votes, making him the fifteenth President of the United States. With this victory, Buchanan became the only President in US history to be elected despite the incumbent president being from the same party and eligible for re-election. Buchanan won 19 out of 31 states (including all of the south), while Frémont took 11 states (all "free states" and in the north), and Fillmore carried just one state; Maryland. The reason for the Democratic Party's dominance in the south was their emphasis on sovereignty, giving states autonomy on the issue of slavery. The Know Nothing Party The ironically titled Native American Party, which began as a secret society, was an anti-Catholic, anti-immigration and xenophobic organization, that became the largest third party in the US in the 1850s. Although they changed their name to the American Party in 1855, they were most commonly known as the "Know Nothing" Party, as when members were asked about specific details regarding the movement they were obliged to reply with "I know nothing". While the party's existence was short-lived, they were the main alternative to the Democratic Party in the south during this time, as the newly-formed Republican Party's anti-slavery stance made them unpopular in the south.

Scholars have long been skeptical of citizens' ability to vote on the basis of their policy views. Voters lack incentives to pay attention to politics and so are often unaware of the policy stances adopted by presidential candidates and parties. However, some scholars have suggested that voter attention may increase when policy issues become important to them, such as when a crisis disrupts their lives. The coronavirus pandemic provides an opportunity to test this proposition. It is one of the most severe crises the United States has faced. It has disrupted almost everyone's lives, and many people know someone who has tested positive or died from the virus. It is thus salient and important to many if not most voters. Despite this context, we find that many voters remain unaware of the candidates' stances on coronavirus policies. Their levels of knowledge are about typical for other policies, which is middling. In the absence of knowledge, voters cannot connect their policy views on the virus with their presidential voting decisions.

This data set contains the voting behaviour of EU member states in public votes of the Council of the EU from 2010 to 2021. Particular attention was given to the following issues: How often did the Council adopt decision by consensus despite voting under qualified majority? Which member states are most often outvoted? Did these pattern change during the Covid-19 pandemic, when the Council had to resort to video meetings? To answer these questions, a new dataset of public data from the EU was cleaned for easy access and analysis. This dataset encompasses all voting data from the public votes in the Council of the EU from January 2010 to November 2021. Due to the rules of procedure of the Council of the EU, only legislative votes are made public. The collected data therefore necessarily encompasses only a limited, self-selected number from all votes in the Council. As of November 23 2021, 1.288 votes are available. Vollerhebung Compilation/SynthesisCompilationSynthesis Kompilation/SyntheseCompilationSynthesis

Roll call voting records for both chambers of the United States Congress through the second session of the 105th Congress are presented in this data collection. Each data file in the collection contains information for one chamber of a single Congress. The units of analysis in each part are the individual members of Congress. Each record contains a member's voting action on every roll call vote taken during that Congress, along with variables that identify the member (e.g., name, party, state, district, uniform ICPSR member number, and most recent means of attaining office). In addition, the codebook provides descriptive information for each roll call, including the date of the vote, outcome in terms of nays and yeas, name of initiator, the relevant bill or resolution number, and a synopsis of the issue.

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.

Abstract (en): CBS News and The New York Times were partners in a series of election surveys covering the 1976 United States presidential election campaign. The surveys were intended to provide another dimension to the political reporting of the two organizations. The surveys, using extensive coverage early in the primary campaign, were designed to monitor the public's changing perception of the candidates, the issues, and the candidates' positions vis-a-vis the issues. Parts 1-9 contain separate nationwide surveys conducted by telephone, with approximately 1,500 randomly selected adults. Five surveys were conducted monthly from February through June, and four more between early September and the general election -- one in September and one following each presidential debate. A final survey was conducted two days after the general election. Respondents were asked for their preferred presidential candidate, their ratings of the candidates' qualifications and positions, and their opinions on a variety of political issues. Part 10, the Election Day Survey, contains a national sample of voters who were interviewed at the polls. Respondents were asked to fill out a questionnaire that asked the name of the presidential candidate for whom they had just voted, and other questions about their political preferences. Part 11 contains data for respondents who were first interviewed in Part 9, Debate Three Survey, and recontacted and reinterviewed for the Post-Election Survey. Data include respondents' voting history, their evaluation of the nominees' positions on various political issues, and their opinions on current political and social issues. Parts 12-26 contain surveys conducted in 12 states on the day of the primary at the polling place, among a random sample of people who had just voted in either the Democratic or Republican presidential primary election. These surveys were conducted in the following primary states: California, Florida, Illinois, Indiana, Massachusetts, Michigan, New Hampshire, New York, Ohio, Pennsylvania, and Wisconsin. There are separate files for the Democratic and Republican primaries in Michigan, Ohio, Indiana, and California, making a total of fifteen primary day "exit" surveys. Respondents were asked whom they voted for and why, the issues that were important in making their choice, and their voting history. Demographic information on respondents in all surveys may include sex, race, age, religion, education, occupation, and labor union affiliation. These files were processed by the Roper Center under a cooperative arrangement with ICPSR. Most of these data were collected by CBS News and The New York Times. The Election Day Survey was conducted solely by CBS News. Parts 1-11 were made available to the ICPSR by CBS News. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Parts 1-6: Persons in households with telephones in the coterminous United States. Parts 7-9 and 11: Registered voters with telephones in the coterminous United States. Parts 10 and 12-26: Voters in the 1976 primary election. (1) These files contain weights, which must be used in any data analysis. (2) There is no card image data for Part 3 and there is only card image data for Parts 11-19. Also, this collection does not contain data for Oregon as the machine-readable documentation indicates.

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.