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Record W4206606421 · doi:10.1177/14789299211064450

Does the Introduction of Online Voting Create Diversity in Representation?

2021· article· en· W4206606421 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePolitical Studies Review · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsVotingBallotRepresentation (politics)Diversity (politics)Political scienceGlobeTurnoutScope (computer science)The InternetElectronic votingPublic relationsRanked voting systemPoliticsPublic administrationInternet privacyPolitical economySociologyComputer sciencePsychologyLawWorld Wide Web

Abstract

fetched live from OpenAlex

The Internet’s effect on political communication is omnipresent. However, very few jurisdictions around the globe allow their citizens to cast their ballot online. What are the electoral consequences of this reform? Research, so far, has mainly looked at security considerations and effects on turnout. In this research note, we broaden the scope of prior studies by examining the effect of online voting on diversity in representation. Using the voting results of municipalities in the Canadian province of Ontario both before and after the implementation of online voting, we test whether this reform has increased the representation of women and youth. We do not find that Internet voting has any significant impact on which candidates are elected, with both the gender and age of elected mayors being constant across online and traditional elections. We further find that the number of woman candidates does not increase with online voting.

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)0.000
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.729
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.449
Teacher spread0.314 · 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