According to exit polling in ten key states of the 2024 presidential election in the United States, ** percent of surveyed white voters reported voting for Donald Trump. In contrast, ** percent of Black voters reported voting for Kamala Harris.

According to exit polling in ten key states of the 2024 presidential election in the United States, Donald Trump received the most support from white voters between the ages of ** and **. In comparison, ** percent of Black voters between the ages of ** and ** reported voting for Kamala Harris.

This web map displays data from the voter registration database as the percent of registered voters by census tract in King County, Washington. The data for this web map is compiled from King County Elections voter registration data for the years 2013-2019. The total number of registered voters is based on the geo-location of the voter's registered address at the time of the general election for each year. The eligible voting population, age 18 and over, is based on the estimated population increase from the US Census Bureau and the Washington Office of Financial Management and was calculated as a projected 6 percent population increase for the years 2010-2013, 7 percent population increase for the years 2010-2014, 9 percent population increase for the years 2010-2015, 11 percent population increase for the years 2010-2016 & 2017, 14 percent population increase for the years 2010-2018 and 17 percent population increase for the years 2010-2019. The total population 18 and over in 2010 was 1,517,747 in King County, Washington. The percentage of registered voters represents the number of people who are registered to vote as compared to the eligible voting population, age 18 and over. The voter registration data by census tract was grouped into six percentage range estimates: 50% or below, 51-60%, 61-70%, 71-80%, 81-90% and 91% or above with an overall 84 percent registration rate. In the map the lighter colors represent a relatively low percentage range of voter registration and the darker colors represent a relatively high percentage range of voter registration. PDF maps of these data can be viewed at King County Elections downloadable voter registration maps. The 2019 General Election Voter Turnout layer is voter turnout data by historical precinct boundaries for the corresponding year. The data is grouped into six percentage ranges: 0-30%, 31-40%, 41-50% 51-60%, 61-70%, and 71-100%. The lighter colors represent lower turnout and the darker colors represent higher turnout. The King County Demographics Layer is census data for language, income, poverty, race and ethnicity at the census tract level and is based on the 2010-2014 American Community Survey 5 year Average provided by the United States Census Bureau. Since the data is based on a survey, they are considered to be estimates and should be used with that understanding. The demographic data sets were developed and are maintained by King County Staff to support the King County Equity and Social Justice program. Other data for this map is located in the King County GIS Spatial Data Catalog, where data is managed by the King County GIS Center, a multi-department enterprise GIS in King County, Washington. King County has nearly 1.3 million registered voters and is the largest jurisdiction in the United States to conduct all elections by mail. In the map you can view the percent of registered voters by census tract, compare registration within political districts, compare registration and demographic data, verify your voter registration or register to vote through a link to the VoteWA, Washington State Online Voter Registration web page.

According to exit polling in ten key states of the 2024 presidential election in the United States, ** percent of surveyed women reported voting for Kamala Harris. In the race to become the next President of the United States, ** percent of men reported voting for Donald Trump.

According to exit polling in the 2020 Presidential Election in the United States, 56 percent of surveyed females reported voting for former Vice President Joe Biden. In the race to become the next president of the United States, 49 percent of men reported voting for incumbent President Donald Trump.

According to exit polling in ten key states of the 2024 presidential election in the United States, Donald Trump received the most support from men between the ages of ** and **. In comparison, ** percent of women between the ages of ** and ** reported voting for Kamala Harris.

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...

AP VoteCast is a survey of the American electorate conducted by NORC at the University of Chicago for Fox News, NPR, PBS NewsHour, Univision News, USA Today Network, The Wall Street Journal and The Associated Press.

AP VoteCast combines interviews with a random sample of registered voters drawn from state voter files with self-identified registered voters selected using nonprobability approaches. In general elections, it also includes interviews with self-identified registered voters conducted using NORC’s probability-based AmeriSpeak® panel, which is designed to be representative of the U.S. population.

Interviews are conducted in English and Spanish. Respondents may receive a small monetary incentive for completing the survey. Participants selected as part of the random sample can be contacted by phone and mail and can take the survey by phone or online. Participants selected as part of the nonprobability sample complete the survey online.

In the 2020 general election, the survey of 133,103 interviews with registered voters was conducted between Oct. 26 and Nov. 3, concluding as polls closed on Election Day. AP VoteCast delivered data about the presidential election in all 50 states as well as all Senate and governors’ races in 2020.

Using this Data - IMPORTANT

This is survey data and must be properly weighted during analysis: DO NOT REPORT THIS DATA AS RAW OR AGGREGATE NUMBERS!!

Instead, use statistical software such as R or SPSS to weight the data.

National Survey

The national AP VoteCast survey of voters and nonvoters in 2020 is based on the results of the 50 state-based surveys and a nationally representative survey of 4,141 registered voters conducted between Nov. 1 and Nov. 3 on the probability-based AmeriSpeak panel. It included 41,776 probability interviews completed online and via telephone, and 87,186 nonprobability interviews completed online. The margin of sampling error is plus or minus 0.4 percentage points for voters and 0.9 percentage points for nonvoters.

State Surveys

In 20 states in 2020, AP VoteCast is based on roughly 1,000 probability-based interviews conducted online and by phone, and roughly 3,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 2.3 percentage points for voters and 5.5 percentage points for nonvoters.

In an additional 20 states, AP VoteCast is based on roughly 500 probability-based interviews conducted online and by phone, and roughly 2,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 2.9 percentage points for voters and 6.9 percentage points for nonvoters.

In the remaining 10 states, AP VoteCast is based on about 1,000 nonprobability interviews conducted online. In these states, the margin of sampling error is about plus or minus 4.5 percentage points for voters and 11.0 percentage points for nonvoters.

Although there is no statistically agreed upon approach for calculating margins of error for nonprobability samples, these margins of error were estimated using a measure of uncertainty that incorporates the variability associated with the poll estimates, as well as the variability associated with the survey weights as a result of calibration. After calibration, the nonprobability sample yields approximately unbiased estimates.

As with all surveys, AP VoteCast is subject to multiple sources of error, including from sampling, question wording and order, and nonresponse.

Sampling Details

Probability-based Registered Voter Sample

In each of the 40 states in which AP VoteCast included a probability-based sample, NORC obtained a sample of registered voters from Catalist LLC’s registered voter database. This database includes demographic information, as well as addresses and phone numbers for registered voters, allowing potential respondents to be contacted via mail and telephone. The sample is stratified by state, partisanship, and a modeled likelihood to respond to the postcard based on factors such as age, race, gender, voting history, and census block group education. In addition, NORC attempted to match sampled records to a registered voter database maintained by L2, which provided additional phone numbers and demographic information.

Prior to dialing, all probability sample records were mailed a postcard inviting them to complete the survey either online using a unique PIN or via telephone by calling a toll-free number. Postcards were addressed by name to the sampled registered voter if that individual was under age 35; postcards were addressed to “registered voter” in all other cases. Telephone interviews were conducted with the adult that answered the phone following confirmation of registered voter status in the state.

Nonprobability Sample

Nonprobability participants include panelists from Dynata or Lucid, including members of its third-party panels. In addition, some registered voters were selected from the voter file, matched to email addresses by V12, and recruited via an email invitation to the survey. Digital fingerprint software and panel-level ID validation is used to prevent respondents from completing the AP VoteCast survey multiple times.

AmeriSpeak Sample

During the initial recruitment phase of the AmeriSpeak panel, randomly selected U.S. households were sampled with a known, non-zero probability of selection from the NORC National Sample Frame and then contacted by mail, email, telephone and field interviewers (face-to-face). The panel provides sample coverage of approximately 97% of the U.S. household population. Those excluded from the sample include people with P.O. Box-only addresses, some addresses not listed in the U.S. Postal Service Delivery Sequence File and some newly constructed dwellings. Registered voter status was confirmed in field for all sampled panelists.

Weighting Details

AP VoteCast employs a four-step weighting approach that combines the probability sample with the nonprobability sample and refines estimates at a subregional level within each state. In a general election, the 50 state surveys and the AmeriSpeak survey are weighted separately and then combined into a survey representative of voters in all 50 states.

State Surveys

First, weights are constructed separately for the probability sample (when available) and the nonprobability sample for each state survey. These weights are adjusted to population totals to correct for demographic imbalances in age, gender, education and race/ethnicity of the responding sample compared to the population of registered voters in each state. In 2020, the adjustment targets are derived from a combination of data from the U.S. Census Bureau’s November 2018 Current Population Survey Voting and Registration Supplement, Catalist’s voter file and the Census Bureau’s 2018 American Community Survey. Prior to adjusting to population totals, the probability-based registered voter list sample weights are adjusted for differential non-response related to factors such as availability of phone numbers, age, race and partisanship.

Second, all respondents receive a calibration weight. The calibration weight is designed to ensure the nonprobability sample is similar to the probability sample in regard to variables that are predictive of vote choice, such as partisanship or direction of the country, which cannot be fully captured through the prior demographic adjustments. The calibration benchmarks are based on regional level estimates from regression models that incorporate all probability and nonprobability cases nationwide.

Third, all respondents in each state are weighted to improve estimates for substate geographic regions. This weight combines the weighted probability (if available) and nonprobability samples, and then uses a small area model to improve the estimate within subregions of a state.

Fourth, the survey results are weighted to the actual vote count following the completion of the election. This weighting is done in 10–30 subregions within each state.

National Survey

In a general election, the national survey is weighted to combine the 50 state surveys with the nationwide AmeriSpeak survey. Each of the state surveys is weighted as described. The AmeriSpeak survey receives a nonresponse-adjusted weight that is then adjusted to national totals for registered voters that in 2020 were derived from the U.S. Census Bureau’s November 2018 Current Population Survey Voting and Registration Supplement, the Catalist voter file and the Census Bureau’s 2018 American Community Survey. The state surveys are further adjusted to represent their appropriate proportion of the registered voter population for the country and combined with the AmeriSpeak survey. After all votes are counted, the national data file is adjusted to match the national popular vote for president.

Data Source: CA Secretary of State

This data biography shares the how, who, what, where, when, and why about this dataset. We, the epidemiology team at Napa County Health and Human Services Agency, Public Health Division, created it to help you understand where the data we analyze and share comes from. If you have any further questions, we can be reached at epidemiology@countyofnapa.org.

Data dashboard featuring this data: Demographics https://data.countyofnapa.org/stories/s/bu3n-fytj

How was the data collected? The California Secretary of State's Elections Division is responsible for maintaining a database of all registered voters as well as coordinating the counting of votes after elections. Voter participation is defined here as the percentage of eligible voters who actually voted.

Who was included and excluded from the data? The term "eligible voters" refers to the population of US citizens aged 18 years or older who currently reside in the voting jurisdiction and who are not in prison or on parole for a felony and who have not been declared mentally incompetent.

Where was the data collected?  Voter registration data and election results are collected throughout California. This subset of data includes Napa County and California.

How often is the data collected? Statewide General Elections are held the Tuesday after the first Monday in November on even years.

Where can I learn more about this data? https://www.sos.ca.gov/elections/prior-elections/statewide-election-results

According to exit polls for the 2024 New Hampshire Republican primary, former President Donald Trump led the way among 59 percent of male voters. The vote was split more evenly among female voters, with Trump receiving 51 percent of the vote, and former South Carolina Governor Nikki Haley receiving 47 percent of the vote. Florida Governor Ron DeSantis remained on the ballot despite dropping out of the race just days prior to the New Hampshire primaries.

This graph shows the percentage of votes of the 2016 presidential elections in the United States on November 9, 2016, by race. According to the exit polls, about 37 percent of white voters voted for Hillary Clinton.

Analysis of ‘🗳 Primary Candidates’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/primary-candidatese on 28 January 2022.

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

About this dataset

This folder contains the data behind the stories:

• We Researched Hundreds Of Races. Here’s Who Democrats Are Nominating.
• How’s The Progressive Wing Doing In Democratic Primaries So Far?
• We Looked At Hundreds Of Endorsements. Here’s Who Republicans Are Listening To.

This project looks at patterns in open Democratic and Republican primary elections for the U.S. Senate, U.S. House and governor in 2018.

dem_candidates.csv contains information about the 811 candidates who have appeared on the ballot this year in Democratic primaries for Senate, House and governor, not counting races featuring a Democratic incumbent, as of August 7, 2018.

rep_candidates.csv contains information about the 774 candidates who have appeared on the ballot this year in Republican primaries for Senate, House and governor, not counting races featuring a Republican incumbent, through September 13, 2018.

Here is a description and source for each column in the accompanying datasets.

dem_candidates.csv and rep_candidates.csv include:

Column	Description
Candidate	All candidates who received votes in 2018’s Democratic primary elections for U.S. Senate, U.S. House and governor in which no incumbent ran. Supplied by Ballotpedia.
State	The state in which the candidate ran. Supplied by Ballotpedia.
District	The office and, if applicable, congressional district number for which the candidate ran. Supplied by Ballotpedia.
Office Type	The office for which the candidate ran. Supplied by Ballotpedia.
Race Type	Whether it was a “regular” or “special” election. Supplied by Ballotpedia.
Race Primary Election Date	The date on which the primary was held. Supplied by Ballotpedia.
Primary Status	Whether the candidate lost (“Lost”) the primary or won/advanced to a runoff (“Advanced”). Supplied by Ballotpedia.
Primary Runoff Status	“None” if there was no runoff; “On the Ballot” if the candidate advanced to a runoff but it hasn’t been held yet; “Advanced” if the candidate won the runoff; “Lost” if the candidate lost the runoff. Supplied by Ballotpedia.
General Status	“On the Ballot” if the candidate won the primary or runoff and has advanced to November; otherwise, “None.” Supplied by Ballotpedia.
Primary %	The percentage of the vote received by the candidate in his or her primary. In states that hold runoff elections, we looked only at the first round (the regular primary). In states that hold all-party primaries (e.g., California), a candidate’s primary percentage is the percentage of the total Democratic vote they received. Unopposed candidates and candidates nominated by convention (not primary) are given a primary percentage of 100 but were excluded from our analysis involving vote share. Numbers come from official results posted by the secretary of state or local elections authority; if those were unavailable, we used unofficial election results from the New York Times.
Won Primary	“Yes” if the candidate won his or her primary and has advanced to November; “No” if he or she lost.

dem_candidates.csv includes:

Column	Description
Gender	“Male” or “Female.” Supplied by Ballotpedia.
Partisan Lean	The FiveThirtyEight partisan lean of the district or state in which the election was held. Partisan leans are calculated by finding the average difference between how a state or district voted in the past two presidential elections and how the country voted overall, with 2016 results weighted 75 percent and 2012 results weighted 25 percent.
Race	“White” if we identified the candidate as non-Hispanic white; “Nonwhite” if we identified the candidate as Hispanic and/or any nonwhite race; blank if we could not identify the candidate’s race or ethnicity. To determine race and ethnicity, we checked each candidate’s website to see if he or she identified as a certain race. If not, we spent no more than two minutes searching online news reports for references to the candidate’s race.
Veteran?	If the candidate’s website says that he or she served in the armed forces, we put “Yes.” If the website is silent on the subject (or explicitly says he or she didn’t serve), we put “No.” If the field was left blank, no website was available.
LGBTQ?	If the candidate’s website says that he or she is LGBTQ (including indirect references like to a same-sex partner), we put “Yes.” If the website is silent on the subject (or explicitly says he or she is straight), we put “No.” If the field was left blank, no website was available.
Elected Official?	We used Ballotpedia, VoteSmart and news reports to research whether the candidate had ever held elected office before, at any level. We put “Yes” if the candidate has held elected office before and “No” if not.
Self-Funder?	We used Federal Election Committee fundraising data (for federal candidates) and state campaign-finance data (for gubernatorial candidates) to look up how much each candidate had invested in his or her own campaign, through either donations or loans. We put “Yes” if the candidate donated or loaned a cumulative $400,000 or more to his or her own campaign before the primary and “No” for all other candidates.
STEM?	If the candidate identifies on his or her website that he or she has a background in the fields of science, technology, engineering or mathematics, we put “Yes.” If not, we put “No.” If the field was left blank, no website was available.
Obama Alum?	We put “Yes” if the candidate mentions working for the Obama administration or campaign on his or her website, or if the candidate shows up on this list of Obama administration members and campaign hands running for office. If not, we put “No.”
Dem Party Support?	“Yes” if the candidate was placed on the DCCC’s Red to Blue list before the primary, was endorsed by the DSCC before the primary, or if the DSCC/DCCC aired pre-primary ads in support of the candidate. (Note: according to the DGA’s press secretary, the DGA does not get involved in primaries.) “No” if the candidate is running against someone for whom one of the above things is true, or if one of those groups specifically anti-endorsed or spent money to attack the candidate. If those groups simply did not weigh in on the race, we left the cell blank.
Emily Endorsed?	“Yes” if the candidate was endorsed by Emily’s List before the primary. “No” if the candidate is running against an Emily-endorsed candidate or if Emily’s List specifically anti-endorsed or spent money to attack the candidate. If Emily’s List simply did not weigh in on the race, we left the cell blank.
Gun Sense Candidate?	“Yes” if the candidate received the Gun Sense Candidate Distinction from Moms Demand Action/Everytown for Gun Safety before the primary, according to media reports or the candidate’s website. “No” if the candidate is running against an candidate with the distinction. If Moms Demand Action simply did not weigh in on the race, we left the cell blank.
Biden Endorsed?	“Yes” if the candidate was endorsed by Joe Biden before the primary. “No” if the candidate is running against a Biden-endorsed candidate or if Biden specifically anti-endorsed the candidate. If Biden simply did not weigh in on the race, we left the cell blank.
Warren Endorsed?	“Yes” if the candidate was endorsed by Elizabeth Warren before the primary. “No” if the candidate is running against a Warren-endorsed candidate or if Warren specifically anti-endorsed the candidate. If Warren simply did not weigh in on the race, we left the cell blank.
Sanders Endorsed?	“Yes” if the candidate was endorsed by Bernie Sanders before the primary. “No” if the candidate is running against a Sanders-endorsed candidate or if Sanders specifically anti-endorsed the candidate. If Sanders simply did not weigh in on the race, we left the cell

Percentage of people who voted in the last federal, provincial and municipal elections, by groups designated as visible minorities and selected sociodemographic characteristics (age group, gender, immigrant status, generation status, first official language spoken and highest certificate, diploma or degree).

According to exit polls from the 2022 midterm election, Republicans won over white voters of both genders in races for the House of Representatives. Black women were the most likely to vote for Democratic candidates in the House of Representatives, with 88 percent saying they voted for a Democrat.

The module was administered as a post-election interview. The resulting data are provided along with voting, demographic, district and macro variables in a single dataset.

CSES Variable List The list of variables is being provided on the CSES Website to help in understanding what content is available from CSES, and to compare the content available in each module.

Themes: MICRO-LEVEL DATA:

Identification and study administration variables: mode of interview; gender of interviewer; date questionnaire administered; election type; weighting factors; if multiple rounds: percent of vote selected parties received in first round; selection of head of state; direct election of head of state and process of direct election; threshold for first-round victory; selection of candidates for the final round; simple majority or absolute majority for 2nd round victory; primary electoral district of respondent; number of days the interview was conducted after the election

Demography: age; gender; education; marital status; union membership; union membership of others in household; business association membership, farmers´ association membership; professional association membership; current employment status; main occupation; socio economic status; employment type - public or private; industrial sector; current employment status, occupation, socio economic status, employment type - public or private and industrial sector of spouse; household income; number of persons in household; number of children in household under the age of 18; attendance at religious services; race; ethnicity; religiosity; religious denomination; language usually spoken at home; region of residence; rural or urban residence

Survey variables: political participation during the recent election campaign (persuade others, campaign activities) and frequency of political participation; contacted by candidate or party during the campaign; respondent cast a ballot at the current and the previous election; vote choice (presidential, lower house and upper house elections) at the current and the previous election; respondent cast candidate preference vote at the current election; most important issue; evaluation of governments performance concerning the most important issue and in general; satisfaction with the democratic process in the country; attitude towards selected statements: it makes a difference who is in power and who people vote for; democracy is better than any other form of government; respondent cast candidate preference vote at the previous election; judgement of the performance of the party the respondent voted for in the previous election; judgement how well voters´ views are represented in elections; party and leader that represent respondent´s view best; form of questionnaire (long or short); party identification; intensity of party identification; sympathy scale for selected parties; assessment of parties and political leaders on a left-right-scale; political participation during the last 5 years: contacted a politician or government, protest or demonstration, work with others who share the same concern; respect for individual freedom and human rights; assessment how much corruption is widespread in the country; self-placement on a left-right-scale; political information items

DISTRICT-LEVEL DATA:

number of seats contested in electoral district, number of candidates, number of party lists, percent vote of different parties, official voter turnout in electoral district

MACRO-LEVEL DATA:

percent of popular vote received by parties in current (lower house/upper house) legislative election; percent of seats in lower house received by parties in current lower house/upper house election; percentage of official voter turnout; number of portfolios held by each party in cabinet, prior to and after the most recent election; year of party foundation; ideological family the parties are closest to; European parliament political group and international organization the parties belong to; significant parties not represented before and after the election; left-right position of parties; general concensus on these left-right placements among informed observers in the country; alternative dimension placements; consensus on the alternative dimension placements; most salient factors in the election; consensus on the salience ranking; electoral alliances permitted during the election campaign; name of alliance and participant parties; number of elected legislative chambers; for lower house and upper house was asked: number of electoral segments; number of primary districts; number of seats; district magnitude (number of members elected from each district); number of secondary and tertiary electoral districts; compulsory voting; votes cast; voting procedure; transferrable votes; cumulated votes if more than one can be cast; party threshold; used electoral formula; party lists close, open, or flexible; parties can run joint lists; possibility of...

Online Voting Software Market Outlook

The global market size for online voting software was valued at approximately USD 342 million in 2023, and it is anticipated to reach USD 1.2 billion by 2032, growing at a robust CAGR of 14.7% during the forecast period. The rapid adoption of digital technologies, combined with the increasing need for secure and efficient voting mechanisms, is a significant factor driving this market's expansion. As societies and organizations strive for more transparent and accessible voting processes, the demand for advanced online voting solutions is set to rise remarkably.

One of the primary growth factors for the online voting software market is the increasing digital transformation across various sectors. Governments, educational institutions, and private organizations are increasingly leveraging digital platforms to streamline their operations and enhance accessibility. The COVID-19 pandemic further accelerated this trend, highlighting the importance of remote and secure voting solutions. The convenience, cost-effectiveness, and security features offered by online voting software make it an attractive option for many end-users, thereby fueling market growth.

Another critical driver of market growth is the rising focus on enhancing voter turnout and participation. Traditional voting methods often pose logistical and accessibility challenges, leading to lower voter engagement. Online voting software addresses these challenges by providing a more accessible and user-friendly platform for voters. The flexibility of voting from any location, coupled with the ability to accommodate diverse voter demographics, significantly boosts voter participation rates. This, in turn, encourages governments and organizations to adopt such systems, propelling market expansion.

The growing emphasis on data security and integrity is also a vital factor in the market's growth. Online voting software incorporates advanced encryption and authentication mechanisms to ensure the security and privacy of voter data. With increasing concerns about cyber threats and election interference, the demand for secure and reliable voting solutions is on the rise. The continuous advancements in cybersecurity technologies and the implementation of stringent regulatory frameworks further support the adoption of online voting software, contributing to market growth.

Regionally, North America holds a significant share of the online voting software market, driven by the early adoption of digital technologies and robust investments in cybersecurity infrastructure. Europe is also witnessing substantial growth, supported by government initiatives to modernize election processes and enhance voter engagement. The Asia Pacific region is expected to experience the fastest growth during the forecast period, attributed to the rapid digitalization and increasing internet penetration in emerging economies. Latin America and the Middle East & Africa regions are gradually adopting online voting solutions, driven by the need for more transparent and efficient voting systems.

Component Analysis

In the online voting software market, the component segment is categorized into software and services. The software segment dominates the market, accounting for the largest share. This segment includes various types of software solutions designed to support electronic voting processes, such as voting management systems, voter registration software, and results tabulation software. The continuous advancements in software technologies, coupled with the increasing demand for user-friendly and secure voting platforms, drive the growth of this segment. Moreover, the deployment of sophisticated software solutions ensures seamless integration with existing electoral systems, further enhancing their adoption.

The services segment encompasses a range of services provided by vendors to support the implementation and operation of online voting systems. These services include consulting, system integration, maintenance, and technical support. The growing complexity of online voting solutions and the need for specialized expertise drive the demand for professional services. Organizations and governments increasingly rely on service providers to ensure the successful deployment and operation of their voting systems, thereby contributing to the growth of the services segment. Additionally, the demand for ongoing support and maintenance services is expected to rise as organizations seek to ensure the reliability and security of their voting systems.

The integration o

Gallup poll (Canadian Institute of Public Opinion) This dataset covers ballots 186-189, and 191, spanning May-July 1949. The dataset contains the data resulting from these polls in ASCII. The ballots are as follows: 186 - May This Gallup Poll aims to collect the political opinions of Canadians, approximately one month before an election. It also attempts to determine how many Canadians will vote, and whether they have decided in advance which party to vote for. Respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. Topics of interest include: car ownership; the federal election; political parties; phone ownership; union membership; and the United Nations; Basic demographic variables are also included. 187 - May This Gallup Poll aims to collect data regarding the political views and opinions of Canadians, as well as their voting patterns. It also measures Canadians' views of government, and compares these views across geographic, demographic and social groups. Topics of interest include: banks; Canadian Pacific Railway; car ownership; communism; the farming industry; the federal election; government ownership of assets; government priorities; housing; immigration; income; the meat packing industry; phone ownership; political party; union membership; and voting behaviour. Basic demographic variables are also included. 188 - June This Gallup Poll aims to measure the opinions of Canadians on topics such as government ownership of assets, and the priorities of the government. It also collects information about voting patterns and preferred political parties, and measures this information across demographic, geographic and social groups. Topics of interest include: banks; Canadian Pacific Railway; car ownership; communism; education; the farm implements industry; freight rates; government ownership of assets; government priorities; immigration; income tax; the iron and steel industry; irrigation; the meat packing industry; political parties; trade; union membership; and voting behaviour. Basic demographic variables are also included. 189 - June This Gallup Poll aims to measure the political views of Canadians and the opinions that Canadians have of political parties before an election. It measures these opinions against the demographic, geographic and social groups of the respondents. Topics of interest include: car ownership; federal election; phone ownership; political party; and union membership. Basic demographics variables are also included. 191 - July This Gallup Poll attempts to measure the opinions of Canadians on such topics as politics, freedom of speech, and education. The survey also contains questions intended to try and measure Canadians' knowledge on different topics concerning their country. Respondents were also asked questions so that they could be grouped \ according to geographic, political and social variables. Topics of interest include: Canada; car ownership; corporal punishment; education of respondents; elections; freedom; free speech; money; phone ownership; political parties; politics; price levels; social security; taxation; travel; union membership; and working conditions in Canada. Basic demographics variables are also included. The codebook for this dataset is available through the UBC Library catalogue, with call number HN110.Z9 P84.

This poll, fielded December 13-17, 2007, is a 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. All of the respondents to this poll were registered voters from South Carolina. The poll included an oversample of African Americans respondents, for a total of 444 African American registered voters. Respondents were asked whether they approved of the way George W. Bush was handling his job as president. Several questions were asked pertaining to the 2008 presidential campaign and the South Carolina presidential primary including how much attention respondents paid to the presidential campaign, the one issue respondents wanted candidates to discuss during the campaign, whether they thought America was ready to elect a Black president, whether they had attended any campaign events, the likelihood respondents would vote in the primary, whether they would vote in the Democratic or Republican primary, and whether the respondent had ever voted in a primary before. Respondents were asked their opinion of presidential candidates Hillary Clinton, John Edwards, Barack Obama, John McCain, Mitt Romney, Rudy Giuliani, Fred Thompson, and Mike Huckabee. Respondents were queried on which candidate they supported, why they supported that specific candidate, whether they had ever supported a different candidate, which candidate they thought had the best chance of winning, whether they thought the candidates had prepared themselves for the job of president, whether they thought each candidate shared the same values of most people in South Carolina, which candidate they thought would bring change to the way things are done in Washington, and which candidate they thought cared most about the needs and problems of Black people. Respondents were also asked which candidate came closest to their own view on illegal immigration, how important it was that a candidate shared their religious beliefs, whether they would vote for a candidate that did not share their views on social issues, and whether they would vote for a candidate that was of a different race, religion, and gender than their own. Questions about the campaigns of Barack Obama and Hillary Clinton addressed the issues of whether Oprah Winfrey's involvement in Obama's campaign made respondents more likely to support Obama, and whether Bill Clinton's involvement in Hillary Clinton's campaign made respondents more likely to support Hillary Clinton. Information was also collected on whether the respondent considered him or herself to be a born-again Christian, whether there were any labor union members in the household, and whether the respondent or any member of the respondent's family served in the armed forces in Iraq. Additional topics in this poll included illegal immigration, Social Security, United States involvement in Iraq, terrorism, and abortion. Demographic information includes sex, age, race, education level, household income, marital status, religious preference, frequency of religious attendance, type of residential area (e.g., urban or rural), political party affiliation, political philosophy, voter registration status and participation history, the presence of children under 18, and labor union member status.

According to exit polling in *** key states of the 2024 presidential election in the United States, almost ********** of voters who had never attended college reported voting for Donald Trump. In comparison, a similar share of voters with ******** degrees reported voting for Kamala Harris.

Question: What share of adult citizens as defined by statute has the legal right to vote in national elections? Clarification: This question does not take into consideration restrictions based on age, residence, having been convicted for crime, or being legally incompetent. It covers legal de jure restrictions, not restrictions that may be operative in practice de facto. The adult population as defined by statute is defined by citizens in the case of independent countries or the people living in the territorial entity in the case of colonies. Universal suffrage is coded as 100%. Universal male suffrage only is coded as 50%. Years before electoral provisions are introduced are scored 0%. The scores do not reflect whether an electoral regime was interrupted or not. Only if new constitutions, electoral laws, or the like explicitly introduce new regulations of suffrage, the scores were adjusted accordingly if the changes suggested doing so. If qualifying criteria other than gender apply such as property, tax payments, income, literacy, region, race, ethnicity, religion, and/or 'economic independence', estimates have been calculated by combining information on the restrictions with different kinds of statistical information on population size, age distribution, wealth distribution, literacy rates, size of ethnic groups, etc., secondary country-specific sources, and --- in the case of very poor information --- the conditions in similar countries or colonies. The scores reflect de jure provisions of suffrage extension in percentage of the adult population. If the suffrage law is revised in a way that affects the extension, the scores reflect this change as of the calendar year the law was enacted. Scale: Interval, from low to high (0-1).