An official website of the United States government
Official 2020 General Election candidate results for all 56 major US jurisdictions -- 50 states, the District of Columbia and the five major territories -- by county (or other major subdivision) including all federal contests and most statewide and state legislative contests. The files are in the common data format (json, version 2) for election results reporting developed by the National Institute of Standards and Technology. The data in these files comes from, or is rolled up to the county level from, files or web pages published by the State, District or Territory Boards of Election. The software used to consolidate the results and export them is in the ElectionDataAnalysis repository. The raw files are available here.
more »
« less
US 2020 General Official Election Results in NIST Common Data Format V2 - xml
Official 2020 General Election candidate results for all 56 major US jurisdictions -- 50 states, the District of Columbia and the five major territories -- by county (or other major subdivision) including all federal contests and most statewide and state legislative contests. The files are in the common data format (xml, version 2) for election results reporting developed by the National Institute of Standards and Technology. The data in these files comes from, or is rolled up to the county level from, files or web pages published by the State, District or Territory Boards of Election. The software used to consolidate the results and export them is in the ElectionDataAnalysis repository. The raw files are available here.
more »
« less
- PAR ID:
- 10312582
- Publisher / Repository:
- Harvard Dataverse
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Official 2020 General Election results for all 56 major US jurisdictions -- 50 states, the District of Columbia and the five major territories -- by county (or other major subdivision) including all federal contests and most statewide and state legislative contests. The files are in tab-separated format. The data in these files comes from, or is rolled up to the county level from, files or web pages published by the State, District or Territory Boards of Election. The software used to consolidate the results and export them is in the ElectionDataAnalysis repository. . The raw files are available here.more » « less
-
Official election results for each of the 50 states, the five major territories and the District of Columbia) for the 2020 General Election. Some files provide results at the precinct level; others have results as the county level (or equivalent for jurisdictions that do not report by county). Contests include all federal contests, most statewide and most state legislative contests. These are the original files from the boards of elections or, where the board of elections provided only pdf or html, the files contain data copied directly en masse from the original files.more » « less
-
The U.S. state of Georgia was central to e!orts to overturn the results of the 2020 Presidential election, including a phone call from then-president Donald Trump to Georgia Secretary of State Brad Ra!ensperger asking Ra!ensperger to ‘find’ 11,780 votes. Ra!ensperger has maintained that a ‘100% full-count risk-limiting audit’ and a machine recount agreed with the initial machine-count results, which proved that the reported election results were accurate and that ‘no votes were flipped.’ While there is no evidence that the reported outcome is wrong, neither is there evidence that it is correct: the two machine counts and the manual ‘audit’ tallies disagree substantially, even about the number of ballots cast. Some ballots in Fulton County, Georgia, were included in the original count at least twice; some were included in the machine recount at least thrice. Audit handcount results for some tally batches were omitted from the reported audit totals: reported audit results do not include all the votes the auditors counted. In short, the two machine counts and the audit were not probative of who won because of poor processes and controls: a lack of secure physical chain of custody, ballot accounting, pollbook reconciliation, and accounting for other election materials such as memory cards. Moreover, most voters used demonstrably untrustworthy ballot-marking devices; as a result, even a perfect handcount or audit would not necessarily reveal who really won. True risk-limiting audits (RLAs) and rigorous recounts can limit the risk that an incorrect electoral outcome will be certified rather than being corrected. But no procedure can limit that risk without a trustworthy record of the vote. And even a properly conducted RLA of some contests in an election does not show that any other contests in that election were decided correctly. The 2020 U.S. Presidential election in Georgia illustrates unrecoverable errors that can render recounts and audits ‘security theater’ that distract from the more serious problems rather than justifying trust.more » « less
-
U.S. elections rely heavily on computers such as voter registration databases, electronic pollbooks, voting machines, scanners, tabulators, and results reporting websites. These introduce digital threats to election outcomes. Risk-limiting audits (RLAs) mitigate threats to some of these systems by manually inspecting random samples of ballot cards. RLAs have a large chance of correcting wrong outcomes (by conducting a full manual tabulation of a trustworthy record of the votes), but can save labor when reported outcomes are correct. This efficiency is eroded when sampling cannot be targeted to ballot cards that contain the contest(s) under audit. If the sample is drawn from all cast cards, then RLA sample sizes scale like the reciprocal of the fraction of ballot cards that contain the contest(s) under audit. That fraction shrinks as the number of cards per ballot grows (i.e., when elections contain more contests) and as the fraction of ballots that contain the contest decreases (i.e., when a smaller percentage of voters are eligible to vote in the contest). States that conduct RLAs of contests on multi-card ballots or RLAs of small contests can dramatically reduce sample sizes by using information about which ballot cards contain which contests—by keeping track of card-style data (CSD). For instance, CSD reduce the expected number of draws needed to audit a single countywide contest on a 4-card ballot by 75%. Similarly, CSD reduce the expected number of draws by 95% or more for an audit of two contests with the same margin on a 4-card ballot if one contest is on every ballot and the other is on 10% of ballots. In realistic examples, the savings can be several orders of magnitude.more » « less
