This dataset contains counts of voter registration and voter turnout for all counties in the United States for the years 2004-2022. It also contains measures of each county's Democratic and Republican partisanship, including six-year longitudinal partisan indices for 2006-2022.

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.

This data collection contains voter registration and turnout surveys. The files contain summaries at state, town, and county levels. Each level of data include: total population, total voting-age population, total voter registration (excluding ND, WI), total ballots cast, total votes cast for president, and voter registration by party. Note: see the documentation for information on missing data.

Dave Leip's website

The Dave Leip website here: https://uselectionatlas.org/BOTTOM/store_data.php lists the available data. Files are occasionally 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. These files were last updated on 9 JUL 2024.

Note that file version numbers are those assigned to them by Dave Leip's Election Atlas. Please refer to the 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_turnout.html.

Similar data may be available at https://www.electproject.org/election-data/voter-turnout-data dating back to 1787.

This dataset contains voter registration data in Iowa by month and county starting with January 2000. It identifies the number of voters registered as Democrats, Republicans, other party or no party. Libertarians were reported separately March 2017 through January 2019, and beginning again in January 2023. The dataset also identifies the number of active and inactive voter registrations. Inactive voters are those to whom official mailings have been sent from the county auditor’s office, the notice was returned as undeliverable by the United States Postal Service and the voter has not responded to a follow up confirmation notice. [§48A.37]

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.

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...

In U.S. presidential elections since 1964, voter turnout among male and female voters has changed gradually but significantly, with women consistently voting at a higher rate than men since the 1980 election. 67 percent of eligible female voters took part in the 1964 election, compared to 72 percent of male voters. This difference has been reversed in recent elections, where the share of women who voted has been larger than the share of men by around four percent since 2004.

Sources

Division of Elections website, https://www.elections.alaska.gov, Number of Registered Voters by Party Within Precinct, September 2023. District numbers were changed due to reapportionment with the U.S. Census 2020.


  Notes



Current precinct maps of those districts lying within the Fairbanks North Star Borough are available at fnsb.gov/elections. Includes only those voters residing within the Fairbanks North Star Borough. Other consists of multiple small parties - refer to source website.

This dataset contains voter registration data in Iowa by month and state senate district starting with June 2021. It identifies the number of voters registered as Democrats, Republicans, other party or no party. The dataset also identifies the number of active and inactive voter registrations. Inactive voters are those to whom official mailings have been sent from the county auditor’s office, the notice was returned as undeliverable by the United States Postal Service and the voter has not responded to a follow up confirmation notice. [§48A.37]

Research suggests that partisans are increasingly avoiding members of the other party—in their choice of neighborhood, social network, even their spouse. Leveraging a national database of voter registration records, we analyze 18 million households in the U.S. We find that three in ten married couples have mismatched party affiliations. We observe the relationship between inter-party marriage and gender, age, and geography. We discuss how the findings bear on key questions of political behavior in the US. Then, we test whether mixed-partisan couples participate less actively in politics. We find that voter turnout is correlated with the party of one’s spouse. A partisan who is married to a co-partisan is more likely to vote. This phenomenon is especially pronounced for partisans in closed primaries, elections in which non-partisan registered spouses are ineligible to participate.

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.

U.S. President general county level voter registration and turnout data for 1992-2022. Each level of data include the following: Total Population (state and county) Total Voting-Age Population (state only) Total Voter Registration (except ND, WI - these two states do not have voter registration.) Total Ballots Cast (for 2004, not yet available for NC, PA. WI doesn't publish this data) Total Vote Cast for President Voter Registration by Party (AK, AZ, CA, CO, CT, DE, DC, FL, IA, KS, KY, LA, MA, ME, MD, NE, NV, NH, NJ, NM, NY, NC, OK, OR, PA, SD, WV, WY). Remaining states do not have voter registration by party). The following worksheets are included in each file: National Summary - summarizes registration and turnout totals by state - with boundary file information (fips) Data by County - data for all counties of all states plus DC - with boundary file information (fips) Data by Town - data for New England towns (ME, MA, CT, RI, VT, NH) - with boundary file information (fips) Data Sources - a list of data sources used to compile the spreadsheet.

March 1995: This survey was conducted by the Los Angeles Times from March 15-19, 1995 on a National sample of 1,007 registered voters. Major topics covered: Clinton job performance; party preference; US economy; Congress; Clinton in the 1996 election; abortion; Republican party politics; race relations; discrimination; affirmative action; Vietnam

October 1995: Right/wrong track; Bill Clinton job performance; party best able; Clinton vs. Congress; confidence in Congress; trusting government; government spending; economy; personal finances; political groups; favorability of political parties; two-party system; Hillary Rodham Clinton; welfare; environment; race relations; marriage; homosexual relations; Roe v. Wade; prayer in schools; moral climate; intolerance; immigration; United Nations; foreign policy; crime; assault weapons ban; own a handgun; on-line computer services; 1996 elections; third party; 1992 election; current employment; born again; the Bible.

February 1997: Direction of country; Bill Clinton job performance; congressional job performance; Clinton vs Republicans in Congress; issue with top priority; economy; Clinton impression; Newt Gingrich impression; State of the Union address; Clinton's proposals; balancing the budget; social security plans; financial health of the Medicare system; proposals to change Medicare; welfare reform bill; Clinton's ethics; Gingrich step down; Gingrich fine; Gingrich's punishment; Democratic National Committee; campaign finance reform bill; Clinton selling presidency; O.J. Simpson verdict; government medical insurance.

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at the Roper Center for Public Opinion Research at https://doi.org/10.25940/ROPER-31093058 and https://doi.org/10.25940/ROPER-31093074. We highly recommend using the Roper Center version as they may make this dataset available in multiple data formats in the future.

This data file does not represent new content, but instead it is the result of merging data from the 2000 NES, the 2002 NES, and the 2004 ANES Panel Study. The 2000 ANES contains questions in areas such as values and predispositions, media exposure, social altruism, and social networks. Special-interest and topical content includes a sizable battery on the Clinton legacy and a smaller retrospective battery on former President George H.W. Bush, new social trust questions specific to neighborhood and workplace, expanded content on civic engagement, questions related to the debate about campaign finance reform, and the first ANES time series appearance of measures on cognitive style. The 2002 ANES contains questions in areas such as social trust and civic engagement. Special-interest and topical content includes questions on the terrorist attacks of September 11, 2001, the war on terrorism, economic inequality, the 2000 Presidential election, recent corporate scandals, the 2001 tax cut, and proposed elimination of the estate tax. The 2004 phase of the panel study was given in large part to questions that capture the likely consequences of the election contest of 2000 and the terrorist attack of September 11th, as understood and interpreted by ordinary Americans. This included instrumentation on participation in political and civic life, satisfaction with democratic institutions, support for administration policy, and views on Afghanistan, Iraq, and homeland security. Demographic variables include sex, race, age, marital status, family income, education level, religious preference, political party affiliation, voter participation history, and registration status.

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.

This study seeks to explain state adoptions of same-day registration, with a focus on determining whether the Democratic (Republican) Party’s support of (resistance to) this impactful voting reform is driven by strategic electoral considerations. I find that states have an increased probability of enacting the reform when legislative Democrats are in the precarious position that comes with having just experienced minority status in one or both chambers. Relatedly, I demonstrate that the presence of a Republican legislature does not make adoption less likely until the size of the Black population reaches a certain threshold. In fact, provided the Black population is small enough, Republican control of the legislature encourages reform. The results offer conflicting evidence, however, that large Latino populations deter the GOP from establishing same-day registration. Considered together, the results cast doubt on the claim that either party’s position is informed by principle alone.

The 2008 National Asian American Survey (NAAS) contains 5,159 completed telephone interviews of self-identified Asian/Asian American residents of the United States. Interviewing began on August 12, 2008, and ended on October 29, 2008. The survey instrument included questions about political behavior and attitudes as well as personal experiences in immigration to the United States. Topics include attitudes toward government, politics and political issues, extent of political involvement, party affiliation, sources of political information, voting behavior, health and financial status, racial and ethnic identification, linked fate and discrimination, and religious and ethnic social networks. The overall length of the interview was approximately 29 minutes. The NAAS includes adults in the United States who identify any family background from countries in Asia, exclusive of countries classified as the Middle East. Survey interviews were conducted in eight languages (English, Cantonese, Mandarin, Korean, Vietnamese, Tagalog, Japanese, and Hindi) -- chosen according to the interviewee's preference -- and yielded sample sizes of at least 500 adult Asian American residents in the six largest national-origin groups. The final breakdown was 1,350 Chinese, 1,150 Asian Indian, 719 Vietnamese, 614 Korean, 603 Filipino, and 541 Japanese origin respondents, with 182 additional respondents who are either from other countries in Asia, or who identify as multi-racial or multi-ethnic. Overall, 40 percent of the sample chose English as their preferred language for the interview. The sample is weighted, using a raking procedure, to reflect the balance of gender, nativity, citizenship status, and educational attainment of the six largest national-origin groups in the United States, as well as the proportion of these national-origin groups within each state. Demographic information includes age, race, language, gender, country of birth, religion, marital status, educational level, employment status, citizenship status, household income, and size of household. Several strategies of sampling were used to collect the data. The largest number of cases were completed interviews drawn from a random selection of respondents in a listed sample of high-probability Asian Americans. This listed sample was drawn from a commercial database of voter registration and marketing, with ethnic propensity classifications based on ethnic names, surnames, and geographic density. Two additional strategies of RDD were used to select respondents, the first from a set of telephone numbers generated to maximize the probability of Filipino Americans, and a second set of telephone numbers generated for the population in general. The general population RDD yielded a very small number of completed interviews relative to contacts made by interviewers (8 out of 1,028 attempts) primarily as a result of the low incidence of the Asian American population in the United States. The sampling design was stratified to collect a disproportionately high number of respondents from "new immigrant destinations" as defined by Audrey Singer of the Brookings Institution. In their raw format, 22 percent of the cases were selected from counties in new destinations while the remaining 78 percent were representative of the United States population. Cases were weighted to account for this stratified sampling design. Additional details about sampling and weighting can be found in the book "Asian American Political Participation: Emerging Constituents and their Political Identities" (Wong, Ramakrishnan, Lee, and Junn. 2011, Publisher: Russell Sage Foundation). Post-stratification weights (NWEIGHTNATYRS) were created using a raking procedure to reflect the balance of gender, nativity, citizenship status, and educational attainment of the six largest national-origin groups in the United States, as well as the proportion of these national-origin groups within each state. More details about the weighting procedure can be found in the book "Asian American Political Participation: Emerging Constituents and their Political Identities" (Wong, Ramakrishnan, Lee, and Junn. 2011, Publisher: Russell Sage Foundation). The universe of analysis contains 5,159 completed telephone interviews of self-identified Asian/Asian American residents of the United States. This is approximately 88 percent of the United States Asian/Asian American adult population. The final breakdown was 1,350 Chinese, 1,150 Asian Indian, 719 Vietnamese, 614 Korean, 603 Filipino, and 541 Japanese origin respondents, with 182 additional respondents who are either from other countries in Asia, or who identify as multi-racial or multi-ethnic. Smallest Geographic Unit: county 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 accom...

The downloadable ZIP file contains Esri shapefiles and PDF maps. Contains the information used to determine the location of the new legislative and congressional district boundaries for the state of Idaho as adopted by Idaho's first Commission on Redistricting on March 9, 2002. Contains viewable and printable legislative and congressional district maps, viewable and printable reports, and importable geographic data files.These data were contributed to INSIDE Idaho at the University of Idaho Library in 2001. CD/DVD -ROM availability: https://alliance-primo.hosted.exlibrisgroup.com/permalink/f/m1uotc/CP71156191150001451These files were created by a six-person, by-partisan commission, consisting of six commission members, three democrats and three republicans. This commission was given 90 days to redraw congressional and legislative district boundaries for the state of Idaho. Due to lawsuits, the process was extended. This legislative plan was approved by the commission on March 9th, 2002 and was previously called L97. All digital data originates from TIGER/Line files and 2000 U.S. Census data.Frequently asked questions:How often are Idaho's legislative and congressional districts redrawn? Once every ten years after each census, as required by law, or when directed by the Idaho Supreme Court. The most recent redistricting followed the 2000 census. Redistricting is not expected to occur again in Idaho until after the 2010 census. Who redrew Idaho's legislative and congressional districts? In 2001, for the first time, Idaho used a citizens' commission to redraw its legislative and congressional district boundaries. Before Idaho voters amended the state Constitution in 1994 to create a Redistricting Commission, redistricting was done by a committee of the Idaho Legislature. The committee's new district plans then had to pass the Legislature before becoming law. Who was on the Redistricting Commission? Idaho's first Commission on Redistricting was composed of Co-Chairmen Kristi Sellers of Chubbuck and Tom Stuart of Boise and Stanley. The other four members were Raymond Givens of Coeur d'Alene, Dean Haagenson of Hayden Lake, Karl Shurtliff of Boise, John Hepworth of Buhl (who resigned effective December 4, 2001), and Derlin Taylor of Burley (who was appointed to replace Mr. Hepworth). What are the requirements for being a Redistricting Commissioner? According to Idaho Law, no person may serve on the commission who: 1. Is not a registered voter of the state at the time of selection; or 2. Is or has been within one (1) year a registered lobbyist; or 3. Is or has been within two (2) years prior to selection an elected official or elected legislative district, county or state party officer. (This requirement does not apply to precinct committeepersons.) The individual appointing authorities may consider additional criteria beyond these statutory requirements. Idaho law also prohibits a person who has served on the Redistricting Commission from serving in either house of the legislature for five years following their service on the commission. When did Idaho's first Commission on Redistricting meet? Idaho law allows the Commission only 90 days to conduct its business. The Redistricting Commission was formed on June 5, 2001. Its 90-day time period would expire on September 3, 2001. After holding hearings around the state in June and July, a majority of the Commission voted to adopt new legislative and congressional districts on August 22, 2001. On November 29th, the Idaho Supreme Court ruled the Commission's legislative redistricting plan unconstitutional and directed them to reconvene and adopt an alternative plan. The Commission did so, adopting a new plan on January 8, 2000. The Idaho Supreme Court found the Commission's second legislative map unconstitutional on March 1, 2002 and ordered the Commission to try again. The Commission adopted a third plan on March 9, 2002. The Supreme Court denied numerous challenges to this third map. It then became the basis for the 2002 primary and General elections and is expected to be used until the 2012 elections. What is the basic timetable for Idaho to redraw its legislative and congressional districts?Typically, and according to Idaho law, the Redistricting Commission cannot be formally convened until after Idaho has received the official census counts and not before June 1 of a year ending in one. Idaho's first Commission on redistricting was officially created on June 5, 2001. By law, a Commission then has 90 days (or until September 3, 2001 in the case of Idaho's first Commission) to approve new legislative and congressional district boundaries based on the most recent census figures. If at least four of the six commissioners fail to approve new legislative and congressional district plans before that 90-day time period expires, the Commission will cease to exist. The law is silent as to what happens next. Could you summarize the important dates for Idaho's first Commission on Redistricting one more time please? After January 1, 2001 but before April 1, 2001: As required by federal law, the Census Bureau must deliver to the states the small area population counts upon which redistricting is based. The Census Bureau determines the exact date within this window when Idaho will get its population figures. Idaho's were delivered on March 23, 2001. Why conduct a census anyway? The original and still primary reason for conducting a national census every ten years is to determine how the 435 seats in the United States House of Representatives are to be apportioned among the 50 states. Each state receives its share of the 435 seats in the U.S. House based on the proportion of its population to that of the total U.S. population. For example, the population shifts during the 1990's resulted in the Northeastern states losing population and therefore seats in Congress to the Southern and the Western states. What is reapportionment? Reapportionment is a federal issue that applies only to Congress. It is the process of dividing up the 435 seats in the U.S. House of Representatives among the 50 states based on each state's proportion of the total U.S. population as determined by the most recent census. Apportionment determines the each state's power, as expressed by the size of their congressional delegation, in Congress and, through the electoral college, directly affects the selection of the president (each state's number of votes in the electoral college equals the number of its representatives and senators in Congress). Like all states, Idaho has two U.S. senators. Based on our 1990 population of 1,006,000 people and our 2000 population of 1,293,953, and relative to the populations of the other 49 states, Idaho will have two seats in the U.S. House of Representatives. Even with the state's 28.5% population increase from 1990 to 2000, Idaho will not be getting a third seat in the U.S. House of Representatives. Assuming Idaho keeps growing at the same rate it did through the decade of the 1990's, it will likely be 30 or 40 years (after 3 or 4 more censuses) before Idaho gets a third congressional seat. What is redistricting? Redistricting is the process of redrawing the boundaries of legislative and congressional districts within each state to achieve population equality among all congressional districts and among all legislative districts. The U.S. Constitution requires this be done for all congressional districts after each decennial census. The Idaho Constitution also requires that this be done for all legislative districts after each census. The democratic principle behind redistricting is "one person, one vote." Requiring that districts be of equal population ensures that every elected state legislator or U.S. congressman represents very close to the same number of people in that state, therefore, each citizen's vote will carry the same weight. How are reapportionment and redistricting related to the census? The original and still primary reason for conducting a census every ten years is to apportion the (now) 435 seats in the U.S. House of Representatives among the several states. The census records population changes and is the legally recognized basis for redrawing electoral districts of equal population. Why is redistricting so important? In a democracy, it is important for all citizens to have equal representation. The political parties also see redistricting as an opportunity to draw districts that favor electing their members and, conversely, that are unfavorable for electing their political opposition. (It's for this reason that redistricting has been described as "the purest form of political bloodsport.") What is PL 94-171? Public Law (PL) 94-171 (Title 13, United States Code) was enacted by Congress in 1975. It was intended to provide state legislatures with small-area census population totals for use in redistricting. The law's origins lie with the "one person, one vote" court decisions in the 1960's. State legislatures needed to reconcile Census Bureau's small geographic area boundaries with voting tabulation districts (precincts) boundaries to create legislative districts with balanced populations. The Census Bureau worked with state legislatures and others to meet this need beginning with the 1980 census. The resulting Public Law 94-171 allows states to work voluntarily with the Census Bureau to match voting district boundaries with small-area census boundaries. With this done, the Bureau can report to those participating states the census population totals broken down by major race group and Hispanic origin for the total population and for persons aged 18 years and older for each census subdivision. Idaho participated in the Bureau's Census 2000 Redistricting Data Program and, where counties used visible features to delineate precinct boundaries, matched those boundaries with census reporting areas. In those instances where counties did not use visible features to

Scholars have long sought to understand the effects of personal exposure to political events on political attitudes and behaviors. This paper takes a fresh look at the long-term effects of exposure to the risk of conscription during the Vietnam War. Like others who have leveraged random assignment to study the effects of conscription and the risk of conscription, we compare men with high and low draft numbers. Our comparisons make use of two data sources. Between 2014 and 2016, we conducted surveys of men whose names and birthdates were public information available through voter registration lists. Birthdates allow us to ascertain their exposure to conscription risk during the three years of the Vietnam draft lotteries. The surveys furnish extensive information about partisanship and policy orientations, especially those pertaining to issues involving the military. We find no appreciable differences between men with high or low draft numbers. These results are confirmed by public voter files, which show no apparent relationship between draft risk and subsequent party affiliation or voter turnout among more than three million draft-eligible men.

This statewide survey of 563 Alabama registered voters collected responses to questions on various topics including the Alabama gubernatorial election, U.S. Senate election, political party images, Alabama taxes, and education.