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Electronic Voting Systems

2019· reference-entry· en· W4252010929 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePolitical Science · 2019
Typereference-entry
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsnot available
Fundersnot available
KeywordsElectronic votingBallotVotingDisapproval votingCardinal voting systemsComputer securityBullet votingComputer scienceInternet privacyProxy votingStraight-ticket votingPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

In 2001, Wand and colleagues published a paper titled “The Butterfly Did It” (see Wand, et al. 2001, cited under Voting System Neutrality) in which they argue that Palm Beach County’s butterfly ballot caused enough errors to decide the 2000 election for George W. Bush. The butterfly ballot also helped launch significant new research initiatives into voting systems and prompted new federal legislation through the Help America Vote Act of 2002, which served to modernize American voting systems. Along with Internet voting, these developments account for most contemporary research on electronic voting systems. Research on electronic voting systems is now at a crossroads. Much of the research following the 2000 election evaluated technology including lever and punch-card machines that are now largely obsolete (Stewart 2011, cited under History and Development of Voting Systems). Current and future research is moving in the direction of issues of security, Internet voting, ballot design, usability, efficiency, and cost of electronic voting systems. All voting systems in the United States today are electronic to a degree. Ansolabehere and Persily 2010 (cited under Empirical and Legal Evaluation of Voting Systems) identifies three discrete parts to voting systems: voter authentication, vote preparation, and vote management. Electronic voting technology can facilitate any of these steps. The term “electronic voting” is polysemous. Electronic voting (or e-voting) variously describes direct-recording electronic voting, electronic vote tabulation, or Internet voting among others. This document defines electronic voting as any voting system that uses electronic technology at any step in the voting process. Fully electronic voting systems use DREs (direct-recording electronic machines), in which ballots are electronically generated, prepared, and counted. Hybrid types of electronic voting are optically scanned ballots (precinct or centrally counted) or ballot mark devices (BMDs), which the voter completes manually and submits but is electronically counted. Electronic voting systems can also include Internet voting in which voters receive, prepare, and submit ballots online. The 2000 presidential election precipitated the most sweeping changes to voting systems, and we continue to see officials adopt new voting systems and Internet voting pilot programs, such as those in Estonia, Canada, Brazil, and Switzerland. Voting systems, particularly Internet voting, are a source of controversy in the United States and abroad. Debates over security and ease of use involve complex technologies and core democratic principles about the rights and responsibilities of citizens. Elections are also, at least in a narrow sense and especially in the United States, zero-sum. Only one person can hold an office, and any change in voting systems that helps one candidate or party necessarily harms the electoral prospects of others. At best, this leads officials to closely scrutinize new voting systems. At worst, it can lead to irreconcilable and unprincipled polarization over questions of voting technology. E-voting involves issues of technology, democratic participation, and electoral politics. This creates a rich environment for research on voting systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0050.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.269
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it